12.1.4.9 Image and Sensor Fusion for Cartography and Aerial Images, Satellite Images, Remote Sensing

Chapter Contents (Back)
Fusion. Sensor Fusion. Cartography. Remote Sensing.
See also Fusion of LANDSAT or Sentinel Images.
See also Fusion of Hyperspectral Images.
See also Pansharpening, Fusion of Aerial Images.
See also Super Resolution for Remote Sensing Applications.

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Clement, V., Giraudon, G., Houzelle, S., Sandakly, F.,
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IEEE Top Reference. BibRef 9307
Earlier:
Interpretation of Remotely Sensed Images in a Context of Multisensor Fusion,
ECCV92(815-819).
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Clement, V., Giraudon, G., Houzelle, S.,
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Elsevier DOI Remote sensing; Image interpolation; POCS: Projections onto convex sets. 0605
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Wald, L., Ranchin, T., Mangolini, M.,
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Wald, L.,
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GeoRS(37), No. 3, May 1999, pp. 1190.
IEEE Top Reference. BibRef 9905

Boo, K.J., Bose, N.K.,
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IEEE Top Reference. 9710
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IJIST(12), No. 1, 2002, pp. 35-42.
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Wen, Y.W.[You-Wei], Ng, M.K.[Michael K.], Ching, W.K.[Wai-Ki],
High-resolution image reconstruction from rotated and translated low-resolution images with multisensors,
IJIST(14), No. 2, 2004, pp. 75-83.
DOI Link 0408
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Ng, M.K.[Michael K.], Bose, N.K.,
Fast color image restoration with multisensors,
IJIST(12), No. 5, 2002, pp. 189-197.
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Ng, M.K.[Michael K.], Kwan, W.C.,
MAP regularized image reconstruction with multisensors,
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IEEE DOI hogh resolution reconstruction BibRef 9900

Jin, Z.M.[Zheng-Meng], Zhang, J.K.[Jun-Kang], Min, L.H.[Li-Hua], Ng, M.K.[Michael K.],
A Variational Model for Spatially Weighting in Image Fusion,
SIIMS(14), No. 2, 2021, pp. 441-469.
DOI Link 2107
BibRef

Ge, H.M.[Huan-Min], Chen, W.[Wengu], Ng, M.K.[Michael K.],
New Restricted Isometry Property Analysis for L_1-L_2 Minimization Methods,
SIIMS(14), No. 2, 2021, pp. 530-557.
DOI Link 2107
BibRef

Huet, F.[Florence], Philipp-Foliguet, S.[Sylvie],
Fusion of Images Interpreted by a New Fuzzy Classifier,
PAA(1), No. 4, 1998, pp. 231-247. BibRef 9800
Earlier:
Fusion of Images after Segmentation by Various Operators and Interpretation by a Multi-Scale Fuzzy Classification,
ICPR98(Vol II: 1843-1845).
IEEE DOI 9808
BibRef
And:
A Multi-Scale Fuzzy Classification by KNN: Application to the Interpretation of Aerial Images,
ICPR98(Vol I: 96-98).
IEEE DOI 9808
BibRef

Zhukov, B.S., Oertel, D.A.,
Modeling of the Fusion of Imaging Spectrometer and Multispectral Scanner Data with a Different Spatial-Resolution,
EORS(14), No. 5, 1997, pp. 723-739. 9804
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Solberg, A.H.S.[Anne H. Schistad],
Contextual Data Fusion Applied to Forest Map Revision,
GeoRS(37), No. 3, May 1999, pp. 1234.
IEEE Top Reference. BibRef 9905
Earlier:
Texture Fusion and Classification Based on Flexible Discriminant Analysis,
ICPR96(II: 596-600).
IEEE DOI 9608
(Norwegian Computing Center, N) BibRef

Price, J.C.,
Combining Multispectral Data of Differing Spatial Resolution,
GeoRS(37), No. 3, May 1999, pp. 1199.
IEEE Top Reference. BibRef 9905

Nielsen, A.A.,
Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data,
IP(11), No. 3, March 2002, pp. 293-305.
IEEE DOI 0203
For data fusion. Transform multispectral data into orthogonal bases BibRef

Melgani, F.[Farid], Serpico, S.B.[Sebastiano B.],
A statistical approach to the fusion of spectral and spatio-temporal contextual information for the classification of remote-sensing images,
PRL(23), No. 9, July 2002, pp. 1053-1061.
Elsevier DOI 0205
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Moser, G., Serpico, S.B.,
Combining Support Vector Machines and Markov Random Fields in an Integrated Framework for Contextual Image Classification,
GeoRS(51), No. 5, May 2013, pp. 2734-2752.
IEEE DOI 1305
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Melgani, F.[Farid], Serpico, S.B.[Sebastiano B.],
A markov random field approach to spatio-temporal contextual image classification,
GeoRS(41), No. 11, November 2003, pp. 2478-2487.
IEEE Abstract. 0311
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Datcu, M., Melgani, F., Piardi, A., Serpico, S.B.,
Multisource data classification with dependence trees,
GeoRS(40), No. 3, March 2002, pp. 609-617.
IEEE Top Reference. 0206
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Ranchin, T.[Thierry], Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano], Wald, L.[Lucien],
Image fusion: The ARSIS concept and some successful implementation schemes,
PandRS(58), No. 1, June 2003, pp. 4-18.
Elsevier DOI 0307
BibRef

Aiazzi, B., Alparone, L., Baronti, S., Cappellini, V., Carlà, R., Mortelli, L.,
Pyramid-based multi-sensor image data fusion with enhancement of textural features,
CIAP97(I: 87-94).
Springer DOI 9709
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Guidi, G., Beraldin, J.A., Ciofi, S., Atzeni, C.,
Fusion of range camera and photogrammetry: A systematic procedure for improving 3-D models metric accuracy,
SMC-B(33), No. 4, August 2003, pp. 667-676.
IEEE Abstract. 0308
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Schiewe, J.[Jochen],
Integration of multi-sensor data for landscape modeling using a region-based approach,
PandRS(57), No. 5-6, April 2003, pp. 371-379.
Elsevier DOI 0307
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Chen, D.M.[Dong-Mei], Stow, D.[Douglas],
Strategies for Integrating Information from Multiple Spatial Resolutions into Land-Use/ Land-Cover Classification Routines,
PhEngRS(69), No. 11, November 2003, pp. 1279-1288.
WWW Link. 0401
Three strategies for integrating image information from different spatial resolutions into classification routines are developed and tested. BibRef

Pinzon, J.E., Pierce, J.F., Tucker, C.J., Brown, M.E.,
Evaluating coherence of natural images by smoothness membership in Besov spaces,
GeoRS(39), No. 9, September 2001, pp. 1879-1889.
IEEE Top Reference. 0111
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Morisette, J.T.[Jeffrey T.], Nickeson, J.E.[Jaime E.], Davis, P.[Paul], Wang, Y.J.[Yu-Jie], Tian, Y.H.[Yu-Hong], Woodcock, C.E.[Curtis E.], Shabanov, N.[Nikolay], Hansen, M.[Matthew], Cohen, W.B.[Warren B.], Oetter, D.R.[Doug R.], Kennedy, R.E.[Robert E.],
High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA Scientific Data Purchase,
RSE(88), No. 1-2, November 2003, pp. 100-110.
Elsevier DOI 0401
BibRef

Shi, W.Z.[Wen-Zhong], Zhu, C.Q.[Chang-Qing], Zhu, C.Y.[Cai-Ying], Yang, X.M.[Xiao-Mei],
Multi-Band Wavelet for Fusing SPOT Panchromatic and Multispectral Images,
PhEngRS(69), No. 5, May 2003, pp. 513-520.
WWW Link. 0307
A three-band wavelet is implemented to fuse 10-m SPOT panchromatic and 30-m multispectral TM images, method is compared with previous methods such as the two-band wavelet and IHS methods for image fusion. BibRef

Shi, W.Z.[Wen-Zhong], Zhu, C.Q.[Chang-Qing], Zhu, S.L.[Shu-Long],
Fusing Ikonos Images by a Four-band Wavelet Transformation Method,
PhEngRS(73), No. 11, November 2007, pp. 1285-1292.
WWW Link. 0709
A fourband wavelet fusion method for fusing one-meter panchromatic and four-meter multispectral imagery. BibRef

Gonzalez-Audicana, M., Saleta, J.L., Catalan, R.G., Garcia, R.,
Fusion of Multispectral and Panchromatic Images Using Improved IHS and PCA Mergers Based on Wavelet Decomposition,
GeoRS(42), No. 6, June 2004, pp. 1291-1299.
IEEE Abstract. 0407
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Maselli, F., Chiesi, M.,
Integration of High- and Low-Resolution Satellite Data to Estimate Pine Forest Productivity in a Mediterranean Coastal Area,
GeoRS(43), No. 1, January 2005, pp. 135-143.
IEEE Abstract. 0501
BibRef

Habib, A.[Ayman], Al-Ruzouq, R.[Rami],
Semi-Automatic Registration of Multi-Source Satellite Imagery with Varying Geometric Resolutions,
PhEngRS(71), No. 3, March 2005, pp. 325-332. A semi-automatic image registration paradigm that can handle multi-source satellite imagery with varying geometric resolutions.
WWW Link. 0509
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Li, Z.H.[Zhen-Hua], Jing, Z.L.[Zhong-Liang], Yang, X.H.[Xu-Hong], Sun, S.Y.[Shao-Yuan],
Color transfer based remote sensing image fusion using non-separable wavelet frame transform,
PRL(26), No. 13, 1 October 2005, pp. 2006-2014.
Elsevier DOI 0509
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Tadesse, T.[Tsegaye], Brown, J.F.[Jesslyn F.], Hayes, M.J.[Michael J.],
A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains,
PandRS(59), No. 4, June 2005, pp. 244-253.
Elsevier DOI 0509
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Gonzalez-Audicana, M., Otazu, X., Fors, O., Alvarez-Mozos, J.,
A Low Computational-Cost Method to Fuse IKONOS Images Using the Spectral Response Function of Its Sensors,
GeoRS(44), No. 6, June 2006, pp. 1683-1691.
IEEE DOI 0606
BibRef

Joshi, M.V., Bruzzone, L., Chaudhuri, S.,
A Model-Based Approach to Multiresolution Fusion in Remotely Sensed Images,
GeoRS(44), No. 9, September 2006, pp. 2549-2562.
IEEE DOI 0609
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Garcia-Haro, F.J., Camacho-de Coca, F., Melia, J.,
A Directional Spectral Mixture Analysis Method: Application to Multiangular Airborne Measurements,
GeoRS(44), No. 2, February 2006, pp. 365-377.
IEEE DOI 0602
Combine multiple signatures. BibRef

Koch, A.[Andreas], Heipke, C.[Christian],
Semantically correct 2.5D GIS data -- The integration of a DTM and topographic vector data,
PandRS(61), No. 1, October 2006, pp. 23-32.
Elsevier DOI 0610
DTM; Integration; Adjustment; Modelling BibRef

Ferguson, R.L.[Randolph L.], Krouse, C.[Charles], Patterson, M.[Marlene], Hare, J.A.[Jonathan A.],
Automated Thematic Registration of NOAA, CoastWatch, and AVHRR Images,
PhEngRS(72), No. 6, June 2006, pp. 677-686.
WWW Link. 0610
Mean radial error less than one pixel was robust to cloud cover. BibRef

Inglada, J., Muron, V., Pichard, D., Feuvrier, T.,
Analysis of Artifacts in Subpixel Remote Sensing Image Registration,
GeoRS(45), No. 1, January 2007, pp. 254-264.
IEEE DOI 0701
BibRef

Pradhan, P.S., King, R.L., Younan, N.H., Holcomb, D.W.,
Estimation of the Number of Decomposition Levels for a Wavelet-Based Multiresolution Multisensor Image Fusion,
GeoRS(44), No. 12, December 2006, pp. 3674-3686.
IEEE DOI 0701
BibRef

Gangkofner, U.G.[Ute G.], Pradhan, P.S.[Pushkar S.], Holcomb, D.W.[Derrold W.],
Optimizing the High-pass Filter Addition Technique for Image Fusion,
PhEngRS(74), No. 9, September 2008, pp. 1107-1118.
WWW Link. 0804
An upgraded methodology for High-Pass adding-based image fusion and comparison of results with wavelet-based image fusion results using spectral and spatial metrics. BibRef

Wong, A.[Alexander], Clausi, D.A.[David A.],
ARRSI: Automatic Registration of Remote-Sensing Images,
GeoRS(45), No. 5, May 2007, pp. 1483-1493.
IEEE DOI 0704
BibRef

Wong, A.[Alexander], Clausi, D.A.[David A.],
AISIR: Automated inter-sensor/inter-band satellite image registration using robust complex wavelet feature representations,
PRL(31), No. 10, 15 July 2010, pp. 1160-1167.
Elsevier DOI 1008
Image registration; Inter-sensor; Inter-band; Complex wavelet feature representations; Remote sensing BibRef

Wong, A.[Alexander],
Simultaneous multi-modal registration of multiple images based on multi-dimensional joint phase moment distributions,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kern, J.P.[Jeffrey P.], Pattichis, M.S.[Marios S.],
Robust Multispectral Image Registration Using Mutual-Information Models,
GeoRS(45), No. 5, May 2007, pp. 1494-1505.
IEEE DOI 0704
BibRef

Kalpoma, K.A., Kudoh, J.I.,
Image Fusion Processing for IKONOS 1-m Color Imagery,
GeoRS(45), No. 10, October 2007, pp. 3075-3086.
IEEE DOI 0711
BibRef

Buntilov, V., Bretschneider, T.R.,
A Content Separation Image Fusion Approach: Toward Conformity Between Spectral and Spatial Information,
GeoRS(45), No. 10, October 2007, pp. 3252-3263.
IEEE DOI 0711
BibRef

Li, R.X.[Rong-Xing], Zhou, F.[Feng], Niu, X.[Xutong], Di, K.C.[Kai-Chang],
Integration of Ikonos and QuickBird Imagery for Geopositioning Accuracy Analysis,
PhEngRS(73), No. 9, September 2007, pp. 1067-1075.
WWW Link. 0709
The integration of Ikonos and QuickBird imagery is feasible and can improve 3D geopositioning accuracy using proper combinations of images. BibRef

Chen, S.H.[Shao-Hui], Su, H.B.[Hong-Bo], Zhang, R.H.[Ren-Hua], Tian, J.[Jing],
Fusing remote sensing images using a trous wavelet transform and empirical mode decomposition,
PRL(29), No. 3, 1 February 2008, pp. 330-342.
Elsevier DOI 0801
Image fusion; A trous wavelet transform; Empirical mode decomposition; Dyadic wavelet transform
See also Depth image enlargement using an evolutionary approach. BibRef

Cakir, H.I.[Halil I.], Khorram, S.[Siamak],
Pixel Level Fusion of Panchromatic and Multispectral Images Based on Correspondence Analysis,
PhEngRS(74), No. 2, February 2008, pp. 183-192.
WWW Link. 0803
A pixel level data fusion approach based on correspondence analysis for high spatial and spectral resolution satellite data. BibRef

Hester, D.B.[David Barry], Cakir, H.I.[Halil I.], Nelson, S.A.C.[Stacy A.C.], Khorram, S.[Siamak],
Per-pixel Classification of High Spatial Resolution Satellite Imagery for Urban Land-cover Mapping,
PhEngRS(74), No. 4, April 2008, pp. 463-472.
WWW Link. 0804
Image fusion, spectral-based classifi cation, and GIS-based map refi nement methods used to derive an urban land-cover map from high spatial resolution satellite data. BibRef

Aanæs, H.[Henrik], Sveinsson, J.R.[Johannes R.], Nielsen, A.A.[Allan Aasbjerg], Bøvith, T.[Thomas], Benediktsson, J.A.[Jón Atli],
Model-Based Satellite Image Fusion,
GeoRS(46), No. 5, May 2008, pp. 1336-1346.
IEEE DOI 0804
BibRef

Gupta, P., Patadia, F., Christopher, S.A.,
Multisensor Data Product Fusion for Aerosol Research,
GeoRS(46), No. 5, May 2008, pp. 1407-1415.
IEEE DOI 0804
BibRef

Santos, C.[Carolina], Messina, J.P.[Joseph P.],
Multi-Sensor Data Fusion for Modeling African Palm in the Ecuadorian Amazon,
PhEngRS(74), No. 6, June 2008, pp. 711-724.
WWW Link. 0711
A significant improvement in the classification accuracy obtained through the fusion of optical and RADARSAT texture measures as compared to single sensor classifications. BibRef

Ancuti, C.[Cosmin], Haber, T.[Tom], Mertens, T.[Tom], Bekaert, P.[Philippe],
Video enhancement using reference photographs,
VC(24), No. 7-9, July 2008, pp. xx-yy.
Springer DOI 0804
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Zhao, Y.Q., Gong, P., Pan, Q.,
Object Detection by Spectropolarimeteric Imagery Fusion,
GeoRS(46), No. 10, October 2008, pp. 3337-3345.
IEEE DOI 0810
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Farah, I.R., Boulila, W., Ettabaa, K.S., Solaiman, B., Ahmed, M.B.,
Interpretation of Multisensor Remote Sensing Images: Multiapproach Fusion of Uncertain Information,
GeoRS(46), No. 12, December 2008, pp. 4142-4152.
IEEE DOI 0812
BibRef

Farah, I.R., Boulila, W., Ettabaa, K.S., Ahmed, M.B.,
Multiapproach System Based on Fusion of Multispectral Images for Land-Cover Classification,
GeoRS(46), No. 12, December 2008, pp. 4153-4161.
IEEE DOI 0812
BibRef

Ghazouani, F., Farah, I.R., Solaiman, B.,
A Multi-Level Semantic Scene Interpretation Strategy for Change Interpretation in Remote Sensing Imagery,
GeoRS(57), No. 11, November 2019, pp. 8775-8795.
IEEE DOI 1911
Semantics, Remote sensing, Visualization, Ontologies, Feature extraction, Data mining, Satellites, Change interpretation, temporal relations BibRef

Boulila, W.[Wadii], Farah, I.R.[Imed Riadh],
Multi-approach Satellite Images Fusion Based On Blind Sources Separation,
IJIG(11), No. 1, January 2011, pp. 117-136.
DOI Link 1103
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Radhadevi, P.V., Solanki, S.S., Jyothi, M.V., Nagasubramanian, V., Varadan, G.[Geeta],
Automated co-registration of images from multiple bands of Liss-4 camera,
PandRS(64), No. 1, January 2009, pp. 17-26.
Elsevier DOI 0804
Co-registration; In-flight calibration; Sensor model; Orbit-aligned; Geo-aligned BibRef

Aksoy, S.[Selim], Koperski, K.[Krzysztof], Tusk, C.[Carsten], Marchisio, G.[Giovanni],
Land Cover Classification with Multi-Sensor Fusion of Partly Missing Data,
PhEngRS(75), No. 5, May 2009, pp. 577-593.
WWW Link. 0904
Decision tree classifiers can be learned with alternative decision nodes for handling missing data in multi-source information fusion where one or more measurements do not exist for some locations. BibRef

Li, Z., Leung, H.,
Fusion of Multispectral and Panchromatic Images Using a Restoration-Based Method,
GeoRS(47), No. 5, May 2009, pp. 1482-1491.
IEEE DOI 0904
BibRef

Saadi, N.M., Aboud, E., Watanabe, K.,
Integration of DEM, ETM+, Geologic, and Magnetic Data for Geological Investigations in the Jifara Plain, Libya,
GeoRS(47), No. 10, October 2009, pp. 3389-3398.
IEEE DOI 0910
BibRef

Flitti, F.[Farid], Collet, C.[Christophe], Slezak, E.,
Image fusion based on pyramidal multiband multiresolution markovian analysis,
SIViP(3), No. 3, September 2009, pp. xx-yy.
Springer DOI 0910
BibRef

Flitti, F.[Farid], Bennamoun, M.[Mohammed], Huynh, D.[Du], Bermak, A.[Amine], Collet, C.[Christophe],
Probabilistic Satellite Image Fusion,
CAIP09(410-418).
Springer DOI 0909
BibRef

Eikvil, L.[Line], Holden, M.[Marit], Huseby, R.B.[Ragnar Bang],
Adaptive Registration of Remote Sensing Images using Supervised Learning,
PhEngRS(75), No. 11, November 2009, pp. 1297-1307.
WWW Link. 1001
A novel approach for registration of time series of remote sensing images, using supervised learning and a region based strategy to adapt the registration to image characteristics. BibRef

Joshi, M., Jalobeanu, A.,
MAP Estimation for Multiresolution Fusion in Remotely Sensed Images Using an IGMRF Prior Model,
GeoRS(48), No. 3, March 2010, pp. 1245-1255.
IEEE DOI 1003
BibRef

Yang, G., Pu, R., Huang, W., Wang, J., Zhao, C.,
A Novel Method to Estimate Subpixel Temperature by Fusing Solar-Reflective and Thermal-Infrared Remote-Sensing Data With an Artificial Neural Network,
GeoRS(48), No. 4, April 2010, pp. 2170-2178.
IEEE DOI 1003
BibRef

Metwalli, M.R.[Mohamed R.], Nasr, A.H.[Ayman H.], Allah, O.S.F.[Osama S. Farag], El-Rabaie, S., El-Samie, F.E.A.[Fathi E. Abd],
Satellite image fusion based on principal component analysis and high-pass filtering,
JOSA-A(27), No. 6, June 2010, pp. 1385-1394.
WWW Link. 1006
BibRef

Fan, X., Rhody, H., Saber, E.,
A Spatial-Feature-Enhanced MMI Algorithm for Multimodal Airborne Image Registration,
GeoRS(48), No. 6, June 2010, pp. 2580-2589.
IEEE DOI 1006
BibRef

Mahyari, A.G., Yazdi, M.,
Fusion of panchromatic and multispectral images using temporal fourier transform,
IET-IPR(4), No. 4, August 2010, pp. 255-260.
DOI Link 1008
BibRef

Ramakrishnan, N., Ertin, E., Moses, R.L.,
Enhancement of Coupled Multichannel Images Using Sparsity Constraints,
IP(19), No. 8, August 2010, pp. 2115-2126.
IEEE DOI 1008
BibRef

Wang, T.H., Fang, C.W., Sung, M.C., Lien, J.J.J.,
Photography Enhancement Based on the Fusion of Tone and Color Mappings in Adaptive Local Region,
IP(19), No. 12, December 2010, pp. 3089-3105.
IEEE DOI 1011
BibRef

Wang, T.H., Chiu, C.W., Wu, W.C., Wang, J.W., Lin, C.Y., Chiu, C.T., Liou, J.J.,
Pseudo-Multiple-Exposure-Based Tone Fusion With Local Region Adjustment,
MultMed(17), No. 4, April 2015, pp. 470-484.
IEEE DOI 1503
Brightness BibRef

Zubko, V., Leptoukh, G.G., Gopalan, A.,
Study of Data-Merging and Interpolation Methods for Use in an Interactive Online Analysis System: MODIS Terra and Aqua Daily Aerosol Case,
GeoRS(48), No. 12, December 2010, pp. 4219-4235.
IEEE DOI 1011

See also Principal Component Analysis of Remote Sensing of Aerosols Over Oceans. BibRef

Saulquin, B., Gohin, F., Garrello, R.,
Regional Objective Analysis for Merging High-Resolution MERIS, MODIS/Aqua, and SeaWiFS Chlorophyll-a Data From 1998 to 2008 on the European Atlantic Shelf,
GeoRS(49), No. 1, January 2011, pp. 143-154.
IEEE DOI 1101
BibRef

Choi, J., Yu, K., Kim, Y.,
A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement,
GeoRS(49), No. 1, January 2011, pp. 295-309.
IEEE DOI 1101
BibRef

Sadhasivam, S.K.[Senthil Kumar], Keerthivasan, M.B.[Mahesh Bharath], Muttan, S.,
Implementation of Max Principle with PCA in image fusion for Surveillance and Navigation Application,
ELCVIA(10), No. 1, 2011, pp. xx-yy.
DOI Link 1112
BibRef

Xu, M.[Min], Chen, H.[Hao], Varshney, P.K.,
An Image Fusion Approach Based on Markov Random Fields,
GeoRS(49), No. 12, December 2011, pp. 5116-5127.
IEEE DOI 1201
BibRef

Brook, A., Ben-Dor, E.,
Automatic Registration of Airborne and Spaceborne Images by Topology Map Matching with SURF Processor Algorithm,
RS(3), No. 1, January 2011, pp. 65-82.
DOI Link 1203
BibRef

Guthier, B.[Benjamin], Kopf, S.[Stephan], Effelsberg, W.[Wolfgang],
Algorithms for a real-time HDR video system,
PRL(34), No. 1, 1 January 2013, pp. 25-33.
Elsevier DOI 1211
BibRef
Earlier:
Histogram-based image registration for real-time high dynamic range videos,
ICIP10(145-148).
IEEE DOI 1009
HDR video; Multi-spectrum video acquisition; Image registration; Video
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Li, S., Yin, H., Fang, L.,
Remote Sensing Image Fusion via Sparse Representations Over Learned Dictionaries,
GeoRS(51), No. 9, 2013, pp. 4779-4789.
IEEE DOI 1309
Dictionaries BibRef

Lee, I.H., Choi, T.S.,
Accurate Registration Using Adaptive Block Processing for Multispectral Images,
CirSysVideo(23), No. 9, 2013, pp. 1491-1501.
IEEE DOI 1309
Accuracy BibRef

Chen, Q.[Qi], Wang, S.[Shugen], Wang, B.[Bo], Sun, M.W.[Ming-Wei],
Automatic Registration Method for Fusion of ZY-1-02C Satellite Images,
RS(6), No. 1, 2013, pp. 157-179.
DOI Link 1402
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Witharana, C.[Chandi], Civco, D.L.[Daniel L.], Meyer, T.H.[Thomas H.],
Evaluation of data fusion and image segmentation in earth observation based rapid mapping workflows,
PandRS(87), No. 1, 2014, pp. 1-18.
Elsevier DOI 1402
Image fusion BibRef

Liang, J.Y.[Jia-Yong], Liu, X.P.[Xiao-Ping], Huang, K.N.[Kang-Ning], Li, X.[Xia], Wang, D.G.[Da-Gang], Wang, X.W.[Xian-Wei],
Automatic Registration of Multisensor Images Using an Integrated Spatial and Mutual Information (SMI) Metric,
GeoRS(52), No. 1, January 2014, pp. 603-615.
IEEE DOI 1402
ant colony optimisation BibRef

Chien, C.L.[Chun-Liang], Tsai, W.H.[Wen-Hsiang],
Image Fusion With No Gamut Problem by Improved Nonlinear IHS Transforms for Remote Sensing,
GeoRS(52), No. 1, January 2014, pp. 651-663.
IEEE DOI 1402
geophysical image processing BibRef

Hu, C.L.[Chu-Li], Li, J.[Jia], Chen, N.C.[Neng-Cheng], Guan, Q.F.[Qing-Feng],
An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation,
RS(6), No. 1, 2014, pp. 677-699.
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Huang, B.[Bo], Song, H.H.[Hui-Hui], Cui, H.B.[Heng-Bin], Peng, J.[Jigen], Xu, Z.B.[Zong-Ben],
Spatial and Spectral Image Fusion Using Sparse Matrix Factorization,
GeoRS(52), No. 3, March 2014, pp. 1693-1704.
IEEE DOI 1403
geophysical image processing BibRef

Garcia-Pedrero, A.[Angel], Gonzalo-Martin, C.[Consuelo], Fonseca-Luengo, D.[David], Lillo-Saavedra, M.[Mario],
A GEOBIA Methodology for Fragmented Agricultural Landscapes,
RS(7), No. 1, 2015, pp. 767-787.
DOI Link 1502
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Chen, B.[Bin], Huang, B.[Bo], Xu, B.[Bing],
Comparison of Spatiotemporal Fusion Models: A Review,
RS(7), No. 2, 2015, pp. 1798-1835.
DOI Link 1503
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Lillo-Saavedra, M.[Mario], Gonzalo-Martín, C.[Consuelo], García-Pedrero, A.[Angel], Lagos, O.[Octavio],
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Zhou, Y.H.[Yu-Hong], Qiu, F.[Fang],
Fusion of high spatial resolution WorldView-2 imagery and LiDAR pseudo-waveform for object-based image analysis,
PandRS(101), No. 1, 2015, pp. 221-232.
Elsevier DOI 1503
Fusion BibRef

Cheng, J.[Jian], Liu, H.J.[Hai-Jun], Liu, T.[Ting], Wang, F.[Feng], Li, H.S.[Hong-Sheng],
Remote sensing image fusion via wavelet transform and sparse representation,
PandRS(104), No. 1, 2015, pp. 158-173.
Elsevier DOI 1505
Remote sensing image fusion BibRef

Gomez-Chova, L., Tuia, D., Moser, G., Camps-Valls, G.,
Multimodal Classification of Remote Sensing Images: A Review and Future Directions,
PIEEE(103), No. 9, September 2015, pp. 1560-1584.
IEEE DOI 1509
Survey, Sensor Fusion. Image fusion BibRef

Mura, M.D.[M. Dalla], Prasad, S., Pacifici, F., Gamba, P., Chanussot, J., Benediktsson, J.A.,
Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing,
PIEEE(103), No. 9, September 2015, pp. 1585-1601.
IEEE DOI 1509
Data integration BibRef

Malleswara Rao, J., Rao, C.V., Senthil Kumar, A., Lakshmi, B., Dadhwal, V.K.,
Spatiotemporal Data Fusion Using Temporal High-Pass Modulation and Edge Primitives,
GeoRS(53), No. 11, November 2015, pp. 5853-5860.
IEEE DOI 1509
edge detection BibRef

Yong, X.Z.[Xuan-Zi], Yang, M.Y.[Michael Ying], Cao, Y.P.[Yan-Peng], Rosenhahn, B.[Bodo],
Descriptor evaluation and feature regression for multimodal image analysis,
MVA(26), No. 7-8, November 2015, pp. 975-990.
Springer DOI 1511
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Earlier: A2, A1, A4, Only:
Feature Regression for Multimodal Image Analysis,
FusionOutdoor14(770-777)
IEEE DOI 1409
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Cerra, D.[Daniele], Bieniarz, J.[Jakub], Müller, R.[Rupert], Storch, T.[Tobias], Reinartz, P.[Peter],
Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing,
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Han, Y.K.[You-Kyung], Bovolo, F., Bruzzone, L.,
An Approach to Fine Coregistration Between Very High Resolution Multispectral Images Based on Registration Noise Distribution,
GeoRS(53), No. 12, December 2015, pp. 6650-6662.
IEEE DOI 1512
deformation BibRef

Han, Y.[Youkyung], Bovolo, F., Bruzzone, L.,
Segmentation-Based Fine Registration of Very High Resolution Multitemporal Images,
GeoRS(55), No. 5, May 2017, pp. 2884-2897.
IEEE DOI 1705
atmospheric optics, image registration, high resolution multitemporal images, homogeneous spectral properties, multiple displacement analysis, multitemporal VHR images,residual local misalignment, segmentation-based fine registration, standard registration, Correlation, Feature extraction, Geometry, Image color analysis, Image resolution, Image segmentation, object representative points, registration, remote sensing, urban areas BibRef

Kim, T.[Taeheon], Han, Y.[Youkyung],
Integrated Preprocessing of Multitemporal Very-High-Resolution Satellite Images via Conjugate Points-Based Pseudo-Invariant Feature Extraction,
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Saha, S., Mou, L., Qiu, C., Zhu, X.X., Bovolo, F., Bruzzone, L.,
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GeoRS(58), No. 12, December 2020, pp. 8780-8792.
IEEE DOI 2012
Image segmentation, Semantics, Image analysis, Feature extraction, Machine learning, Data mining, Training, Deep learning, segmentation BibRef

Wu, B.[Bo], Huang, B.[Bo], Zhang, L.P.[Liang-Pei],
An Error-Bound-Regularized Sparse Coding for Spatiotemporal Reflectance Fusion,
GeoRS(53), No. 12, December 2015, pp. 6791-6803.
IEEE DOI 1512
data acquisition BibRef

Bai, K.X.[Kai-Xu], Chang, N.B.[Ni-Bin], Chen, C.F.[Chi-Farn],
Spectral Information Adaptation and Synthesis Scheme for Merging Cross-Mission Ocean Color Reflectance Observations From MODIS and VIIRS,
GeoRS(54), No. 1, January 2016, pp. 311-329.
IEEE DOI 1601
ocean composition BibRef

Joshi, N.[Neha], Baumann, M.[Matthias], Ehammer, A.[Andrea], Fensholt, R.[Rasmus], Grogan, K.[Kenneth], Hostert, P.[Patrick], Jepsen, M.R.[Martin Rudbeck], Kuemmerle, T.[Tobias], Meyfroidt, P.[Patrick], Mitchard, E.T.A.[Edward T. A.], Reiche, J.[Johannes], Ryan, C.M.[Casey M.], Waske, B.[Björn],
A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring,
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Award, Remote Sensing, Third. BibRef

Scheffler, D.[Daniel], Hollstein, A.[André], Diedrich, H.[Hannes], Segl, K.[Karl], Hostert, P.[Patrick],
AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data,
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Code, Registration. BibRef

Wang, L.[Likun], Tremblay, D.[Denis], Zhang, B.[Bin], Han, Y.[Yong],
Fast and Accurate Collocation of the Visible Infrared Imaging Radiometer Suite Measurements with Cross-Track Infrared Sounder,
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Zhang, Y.H.[Yu-Hang], Prasad, S.[Saurabh],
Multisource Geospatial Data Fusion via Local Joint Sparse Representation,
GeoRS(54), No. 6, June 2016, pp. 3265-3276.
IEEE DOI 1606
geophysical image processing BibRef

Montzka, C., Jagdhuber, T., Horn, R., Bogena, H.R., Hajnsek, I., Reigber, A., Vereecken, H.,
Investigation of SMAP Fusion Algorithms With Airborne Active and Passive L-Band Microwave Remote Sensing,
GeoRS(54), No. 7, July 2016, pp. 3878-3889.
IEEE DOI 1606
L-band BibRef

Ling, X.[Xiao], Zhang, Y.J.[Yong-Jun], Xiong, J.X.[Jin-Xin], Huang, X.[Xu], Chen, Z.P.[Zhi-Peng],
An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery,
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McDowell, M.L.[Meryl L.], Kruse, F.A.[Fred A.],
Enhanced Compositional Mapping through Integrated Full-Range Spectral Analysis,
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DOI Link 1610
integration of visible to near infrared, shortwave infrared, and longwave infrared. BibRef

Shen, H., Meng, X., Zhang, L.,
An Integrated Framework for the Spatio-Temporal-Spectral Fusion of Remote Sensing Images,
GeoRS(54), No. 12, December 2016, pp. 7135-7148.
IEEE DOI 1612
geophysical image processing BibRef

Shen, H.,
Integrated Fusion Method For Multiple Temporal-spatial-spectral Images,
ISPRS12(XXXIX-B7:407-410).
DOI Link 1209
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Xu, X.C.[Xiao-Cong], Li, X.[Xia], Liu, X.P.[Xiao-Ping], Shen, H.F.[Huan-Feng], Shi, Q.[Qian],
Multimodal registration of remotely sensed images based on Jeffrey's divergence,
PandRS(122), No. 1, 2016, pp. 97-115.
Elsevier DOI 1612
Multimodal image registration BibRef

Zhao, M., An, B., Wu, Y., Van Luong, H., Kaup, A.,
RFVTM: A Recovery and Filtering Vertex Trichotomy Matching for Remote Sensing Image Registration,
GeoRS(55), No. 1, January 2017, pp. 375-391.
IEEE DOI 1701
error analysis BibRef

Zhao, M., Wu, Y., Pan, S., Zhou, F., An, B., Kaup, A.,
Automatic Registration of Images With Inconsistent Content Through Line-Support Region Segmentation and Geometrical Outlier Removal,
IP(27), No. 6, June 2018, pp. 2731-2746.
IEEE DOI 1804
feature extraction, image matching, image registration, image segmentation, radar imaging, remote sensing, scale invariant feature transformation BibRef

Wei, J.B.[Jing-Bo], Wang, L.Z.[Li-Zhe], Liu, P.[Peng], Song, W.J.[Wei-Jing],
Spatiotemporal Fusion of Remote Sensing Images with Structural Sparsity and Semi-Coupled Dictionary Learning,
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DOI Link 1702
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Chen, B.[Bin], Huang, B.[Bo], Xu, B.[Bing],
Multi-source remotely sensed data fusion for improving land cover classification,
PandRS(124), No. 1, 2017, pp. 27-39.
Elsevier DOI 1702
Land cover classification BibRef

Nguyen, H.[Hai], Cressie, N.[Noel], Braverman, A.[Amy],
Multivariate Spatial Data Fusion for Very Large Remote Sensing Datasets,
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DOI Link 1703
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Ye, Y., Shan, J., Bruzzone, L., Shen, L.,
Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity,
GeoRS(55), No. 5, May 2017, pp. 2941-2958.
IEEE DOI 1705
image matching, image registration, optical radar, remote sensing, synthetic aperture radar, LiDAR, SAR, automatic image registration, fast template matching scheme, feature descriptor, histogram of orientated phase congruency, light detection and ranging, map data, normalized correlation coefficient, optical radar, BibRef

Yang, K.[Kun], Pan, A.N.[An-Ning], Yang, Y.[Yang], Zhang, S.[Su], Ong, S.H.[Sim Heng], Tang, H.L.[Hao-Lin],
Remote Sensing Image Registration Using Multiple Image Features,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
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Yan, K.[Kai], Dong, Y.X.[Ya-Xin], Yang, Y.[Yang], Xing, L.[Lin],
Multi-SUAV Collaboration and Low-Altitude Remote Sensing Technology-Based Image Registration and Change Detection Network of Garbage Scattered Areas in Nature Reserves,
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Cheng, Q.[Qing], Liu, H.Q.[Hui-Qing], Shen, H.F.[Huan-Feng], Wu, P.H.[Peng-Hai], Zhang, L.P.[Liang-Pei],
A Spatial and Temporal Nonlocal Filter-Based Data Fusion Method,
GeoRS(55), No. 8, August 2017, pp. 4476-4488.
IEEE DOI 1708
Data integration, Monitoring, Remote sensing, Sensors, Spatial resolution, Spatiotemporal phenomena, Data fusion, nonlocal, reflectance prediction, similarity information, spatiotemporal BibRef

Chaib, S., Liu, H., Gu, Y., Yao, H.,
Deep Feature Fusion for VHR Remote Sensing Scene Classification,
GeoRS(55), No. 8, August 2017, pp. 4775-4784.
IEEE DOI 1708
Correlation, Feature extraction, Image resolution, Machine learning, Principal component analysis, Remote sensing, Visualization, Discriminant correlation analysis (DCA), features fusion, scene classification, unsupervised, features, learning BibRef

Zeng, C.Q.[Chui-Qing], King, D.J.[Douglas J.], Richardson, M.[Murray], Shan, B.[Bo],
Fusion of Multispectral Imagery and Spectrometer Data in UAV Remote Sensing,
RS(9), No. 7, 2017, pp. xx-yy.
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Shi, Z.K.[Zhong-Kui], Li, P.J.[Pei-Jun], Jin, H.[Huiran], Tian, Y.G.[Yu-Gang], Chen, Y.[Yan], Zhang, X.F.[Xian-Feng],
Improving Super-Resolution Mapping by Combining Multiple Realizations Obtained Using the Indicator-Geostatistics Based Method,
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Yanovsky, I.[Igor], Behrangi, A.[Ali], Wen, Y.X.[Yi-Xin], Schreier, M.[Mathias], Dang, V.[Van], Lambrigtsen, B.[Bjorn],
Enhanced Resolution of Microwave Sounder Imagery through Fusion with Infrared Sensor Data,
RS(9), No. 11, 2017, pp. xx-yy.
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Sidiropoulos, P.[Panagiotis], Muller, J.P.[Jan-Peter],
A Systematic Solution to Multi-Instrument Coregistration of High-Resolution Planetary Images to an Orthorectified Baseline,
GeoRS(56), No. 1, January 2018, pp. 78-92.
IEEE DOI 1801
Cameras, Estimation, Image matching, Image resolution, Mars, Remote sensing, Systematics, High-resolution imaging, remote sensing BibRef

Zhang, W.K.[Wen-Kai], Huang, H.[Hai], Schmitz, M.[Matthias], Sun, X.[Xian], Wang, H.Q.[Hong-Qi], Mayer, H.[Helmut],
Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling,
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Xue, J.[Jie], Leung, Y.[Yee], Fung, T.[Tung],
A Bayesian Data Fusion Approach to Spatio-Temporal Fusion of Remotely Sensed Images,
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Xue, J.[Jie], Leung, Y.[Yee], Fung, T.[Tung],
An Unmixing-Based Bayesian Model for Spatio-Temporal Satellite Image Fusion in Heterogeneous Landscapes,
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He, H.Q.[Hai-Qing], Chen, M.[Min], Chen, T.[Ting], Li, D.J.[Da-Jun],
Matching of Remote Sensing Images with Complex Background Variations via Siamese Convolutional Neural Network,
RS(10), No. 2, 2018, pp. xx-yy.
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Zhu, X.L.[Xiao-Lin], Cai, F.Y.[Fang-Yi], Tian, J.Q.[Jia-Qi], Williams, T.K.A.[Trecia Kay-Ann],
Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions,
RS(10), No. 4, 2018, pp. xx-yy.
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Zhao, X.Y.[Xiao-Yang], Zhang, J.[Jian], Yang, C.H.[Cheng-Hai], Song, H.B.[Huai-Bo], Shi, Y.Y.[Ye-Yin], Zhou, X.G.[Xin-Gen], Zhang, D.Y.[Dong-Yan], Zhang, G.Z.[Guo-Zhong],
Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification,
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Wan, W.G.[Wei-Guo], Yang, Y.[Yong], Lee, H.J.[Hyo Jong],
Practical remote sensing image fusion method based on guided filter and improved SML in the NSST domain,
SIViP(12), No. 5, July 2018, pp. 959-966.
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Ying, H.C.[Han-Chi], Leung, Y.[Yee], Cao, F.L.[Fei-Long], Fung, T.[Tung], Xue, J.[Jie],
Sparsity-Based Spatiotemporal Fusion via Adaptive Multi-Band Constraints,
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Belgiu, M.[Mariana], Stein, A.[Alfred],
Spatiotemporal Image Fusion in Remote Sensing,
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Polewski, P.[Przemyslaw], Yao, W.[Wei],
Scale invariant line-based co-registration of multimodal aerial data using L1 minimization of spatial and angular deviations,
PandRS(152), 2019, pp. 79-93.
Elsevier DOI 1905
Coregistration, Gable roof lines, Urban areas, Graph matching, Suburban areas BibRef

Ghahremani, M.[Morteza], Liu, Y.H.[Yong-Huai], Yuen, P.[Peter], Behera, A.[Ardhendu],
Remote sensing image fusion via compressive sensing,
PandRS(152), 2019, pp. 34-48.
Elsevier DOI 1905
Pan-sharpening, Compressive sensing, Multiscale dictionary, Panchromatic data, Multispectral data BibRef

Vargas, E., Arguello, H., Tourneret, J.,
Spectral Image Fusion From Compressive Measurements Using Spectral Unmixing and a Sparse Representation of Abundance Maps,
GeoRS(57), No. 7, July 2019, pp. 5043-5053.
IEEE DOI 1907
Image coding, Spatial resolution, Sensors, Imaging, Image fusion, Fuses, Compressive sampling, data fusion, remote sensing, spectral imaging BibRef

Ramirez, J.M.[Juan Marcos], Arguello, H.[Henry],
Multiresolution Compressive Feature Fusion for Spectral Image Classification,
GeoRS(57), No. 12, December 2019, pp. 9900-9911.
IEEE DOI 1912
Feature extraction, Image coding, Apertures, Sensors, Optical imaging, Image resolution, spectral image classification BibRef

Ramirez, J.M.[Juan Marcos], Martínez Torre, J.I.[José Ignacio], Arguello, H.[Henry],
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SP:IC(90), 2021, pp. 116014.
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Compressive spectral imaging, Dual-resolution acquisition systems, Feature fusion, Spectral image classification BibRef

Song, S.[Shiran], Liu, J.H.[Jian-Hua], Pu, H.[Heng], Liu, Y.[Yuan], Luo, J.Y.[Jing-Yan],
The Comparison of Fusion Methods for HSRRSI Considering the Effectiveness of Land Cover (Features) Object Recognition Based on Deep Learning,
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Liu, X.[Xun], Deng, C.W.[Chen-Wei], Chanussot, J.[Jocelyn], Hong, D.F.[Dan-Feng], Zhao, B.J.[Bao-Jun],
StfNet: A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion,
GeoRS(57), No. 9, September 2019, pp. 6552-6564.
IEEE DOI 1909
Spatial resolution, Spatiotemporal phenomena, Remote sensing, Earth, Convolutional neural networks, Image fusion, temporal dependence (TD) BibRef

Fung, C.H.[Che Heng], Wong, M.S.[Man Sing], Chan, P.W.,
Spatio-Temporal Data Fusion for Satellite Images Using Hopfield Neural Network,
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Li, X.J.[Xian-Ju], Tang, Z.[Zhuang], Chen, W.T.[Wei-Tao], Wang, L.[Lizhe],
Multimodal and Multi-Model Deep Fusion for Fine Classification of Regional Complex Landscape Areas Using ZiYuan-3 Imagery,
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Guan, H.C.[Hong-Can], Su, Y.J.[Yan-Jun], Hu, T.Y.[Tian-Yu], Chen, J.[Jin], Guo, Q.H.[Qing-Hua],
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Zhang, C.M.[Cheng-Ming], Chen, Y.[Yan], Yang, X.X.[Xiao-Xia], Gao, S.[Shuai], Li, F.[Feng], Kong, A.[Ailing], Zu, D.W.[Da-Wei], Sun, L.[Li],
Improved Remote Sensing Image Classification Based on Multi-Scale Feature Fusion,
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Efficient Discrimination and Localization of Multimodal Remote Sensing Images Using CNN-Based Prediction of Localization Uncertainty,
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Schmitt, A.[Andreas], Wendleder, A.[Anna], Kleynmans, R.[Rüdiger], Hell, M.[Maximilian], Roth, A.[Achim], Hinz, S.[Stefan],
Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases,
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Fu, G.P.[Guan-Peng], Hong, S.H.[Shao-Hua], Li, F.L.[Fu-Lin], Wang, L.[Lin],
A novel multi-focus image fusion method based on distributed compressed sensing,
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Elsevier DOI 2004
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Earlier: A3, A2, A4, Only:
A New Satellite Image Fusion Method Based on Distributed Compressed Sensing,
ICIP18(1882-1886)
IEEE DOI 1809
Distributed compressed sensing, Decision map, Multi-focus image fusion, Joint-sparsity-model-1. Dictionaries, Sensors, Spatial resolution, Satellites, Matching pursuit algorithms, satellite image fusion BibRef

Du, X., Zare, A.,
Multiresolution Multimodal Sensor Fusion for Remote Sensing Data With Label Uncertainty,
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IEEE DOI 2004
Laser radar, Remote sensing, Spatial resolution, Uncertainty, Fuses, Choquet integral (CI), sensor fusion BibRef

Kizel, F.[Fadi], Benediktsson, J.A.[Jón Atli],
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Hou, S.[Shuwei], Sun, W.F.[Wen-Fang], Guo, B.L.[Bao-Long], Li, C.[Cheng], Li, X.B.[Xiao-Bo], Shao, Y.Z.[Ying-Zhao], Zhang, J.H.[Jian-Hua],
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Shahi, K.R.[Kasra Rafiezadeh], Ghamisi, P.[Pedram], Rasti, B.[Behnood], Jackisch, R.[Robert], Scheunders, P.[Paul], Gloaguen, R.[Richard],
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DOI Link 2012
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Ye, X.H.[Xin-Hai], Xiong, F.C.[Feng-Chao], Lu, J.F.[Jian-Feng], Zhou, J.[Jun], Qian, Y.T.[Yun-Tao],
F3-Net: Feature Fusion and Filtration Network for Object Detection in Optical Remote Sensing Images,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zhang, Y.[Yi], Fu, L.[Lei], Li, Y.[Ying], Zhang, Y.N.[Yan-Ning],
HDFNet: Hierarchical Dynamic Fusion Network for Change Detection in Optical Aerial Images,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, Y.C.[Yan-Chao], Yang, W.[Wen], Sun, Y.[Ying], Chang, C.[Christine], Yu, J.[Jiya], Zhang, W.B.[Wen-Bo],
Fusion of Multispectral Aerial Imagery and Vegetation Indices for Machine Learning-Based Ground Classification,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
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Zhang, H.Y.[Hong-Yan], Song, Y.Y.[Yi-Yao], Han, C.[Chang], Zhang, L.P.[Liang-Pei],
Remote Sensing Image Spatiotemporal Fusion Using a Generative Adversarial Network,
GeoRS(59), No. 5, May 2021, pp. 4273-4286.
IEEE DOI 2104
Spatial resolution, Remote sensing, Earth, Spatiotemporal phenomena, Artificial satellites, Generators, spatiotemporal fusion BibRef

Iyer, G.[Geoffrey], Chanussot, J.[Jocelyn], Bertozzi, A.L.[Andrea L.],
A Graph-Based Approach for Data Fusion and Segmentation of Multimodal Images,
GeoRS(59), No. 5, May 2021, pp. 4419-4429.
IEEE DOI 2104
Image segmentation, Laser radar, Data integration, Laplace equations, Optical imaging, Optical sensors, Graphs, segmentation BibRef

Zheng, Z.G.[Zhong-Gang], Li, Q.M.[Qing-Mei], Fu, K.[Kun],
Evaluation Model of Remote Sensing Satellites Cooperative Observation Capability,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Shi, C.P.[Cui-Ping], Zhao, X.[Xin], Wang, L.G.[Li-Guo],
A Multi-Branch Feature Fusion Strategy Based on an Attention Mechanism for Remote Sensing Image Scene Classification,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
Remote Sensing Scene Image Classification Based on Dense Fusion of Multi-level Features,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Channel Multi-Group Fusion for Remote Sensing Scene Classification,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Wang, T.Y.[Tian-Yi], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Hierarchical-Wise Convolution Fusion for Remote-Sensing Scene Image Classification,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
Remote Sensing Scene Image Classification Based on Self-Compensating Convolution Neural Network,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Shi, C.P.[Cui-Ping], Ding, M.X.[Meng-Xiang], Wang, L.G.[Li-Guo], Pan, H.Z.[Hai-Zhu],
Learn by Yourself: A Feature-Augmented Self-Distillation Convolutional Neural Network for Remote Sensing Scene Image Classification,
RS(15), No. 23, 2023, pp. 5620.
DOI Link 2312
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Group-Wise Hybrid Attention for Remote Sensing Scene Classification,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Lin, J.Z.[Jian-Zhe], Yu, T.Z.[Tian-Ze], Mou, L.C.[Li-Chao], Zhu, X.X.[Xiao-Xiang], Ward, R.K.[Rabab Kreidieh], Wang, Z.J.[Z. Jane],
Unifying Top-Down Views by Task-Specific Domain Adaptation,
GeoRS(59), No. 6, June 2021, pp. 4689-4702.
IEEE DOI 2106
Task analysis, Generators, Data models, Correlation, Satellites, Semantics, Adaptation models, machine learning-predictive models BibRef

Lu, H.[Han], Qiao, D.Y.[Dan-Yu], Li, Y.X.[Yong-Xin], Wu, S.[Shuang], Deng, L.[Lei],
Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used?,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Koz, A.[Alper], Efe, U.[Ufuk],
Geometric- and Optimization-Based Registration Methods for Long-Wave Infrared Hyperspectral Images,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Luo, X.[Xin], Tong, X.H.[Xiao-Hua], Hu, Z.W.[Zhong-Wen],
Improving Satellite Image Fusion via Generative Adversarial Training,
GeoRS(59), No. 8, August 2021, pp. 6969-6982.
IEEE DOI 2108
Image fusion, Satellites, Training, Spatial resolution, Remote sensing, Deep learning, Sentinel-2 BibRef

Zhao, X.[Xin], Li, H.[Hui], Wang, P.[Ping], Jing, L.H.[Lin-Hai],
An Image Registration Method Using Deep Residual Network Features for Multisource High-Resolution Remote Sensing Images,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, S.Y.[Si-Yuan], Jiao, J.N.[Jian-Nan], Wang, C.[Chi],
Research on Polarized Multi-Spectral System and Fusion Algorithm for Remote Sensing of Vegetation Status at Night,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Nara, H.[Hideharu], Sawada, Y.[Yohei],
Global Change in Terrestrial Ecosystem Detected by Fusion of Microwave and Optical Satellite Observations,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, L.Z.[Liang-Zhi], Han, L.[Ling], Ding, M.T.[Ming-Tao], Cao, H.Y.[Hong-Ye], Hu, H.J.[Hui-Juan],
A deep learning semantic template matching framework for remote sensing image registration,
PandRS(181), 2021, pp. 205-217.
Elsevier DOI 2110
Registration, Deep learning, Semantic template, Semantic distribution probability, Remote sensing image, CNN BibRef

Stone, D.L.[David L.], Ravi, S.[Sumved], Benli, E.[Emrah], Motai, Y.I.[Yu-Ichi],
DeepFuseNet of Omnidirectional Far-Infrared and Visual Stream for Vegetation Detection,
GeoRS(59), No. 11, November 2021, pp. 9057-9070.
IEEE DOI 2111
Visualization, Feature extraction, Robots, Sensors, Vegetation mapping, Cameras, Sensor fusion, vegetation detection BibRef

Liu, Q.J.[Qing-Jie], Zhou, H.Y.[Huan-Yu], Xu, Q.Z.[Qi-Zhi], Liu, X.Y.[Xiang-Yu], Wang, Y.H.[Yun-Hong],
PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening,
GeoRS(59), No. 12, December 2021, pp. 10227-10242.
IEEE DOI 2112
BibRef
Earlier: A4, A5, A1, Only: ICIP18(873-877)
IEEE DOI 1809
BibRef
And: A4, A5, A1, Only:
Remote Sensing Image Fusion Based on Two-Stream Fusion Network,
MMMod18(I:428-439).
Springer DOI 1802
Generative adversarial networks, Generators, Neural networks, Training, Spatial resolution, Data models, residual learning. Remote sensing, Task analysis, Image fusion, pan-sharpening, GAN, remote sensing BibRef

Tan, Z.Y.[Zhen-Yu], Gao, M.L.[Mei-Ling], Li, X.H.[Xing-Hua], Jiang, L.C.[Liang-Cun],
A Flexible Reference-Insensitive Spatiotemporal Fusion Model for Remote Sensing Images Using Conditional Generative Adversarial Network,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Spatiotemporal phenomena, Data models, Remote sensing, Image resolution, Spatial resolution, spatiotemporal BibRef

Sun, W.W.[Wei-Wei], Ren, K.[Kai], Meng, X.C.[Xiang-Chao], Xiao, C.C.[Chen-Chao], Yang, G.[Gang], Peng, J.T.[Jiang-Tao],
A Band Divide-and-Conquer Multispectral and Hyperspectral Image Fusion Method,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Spatial resolution, Neural networks, Image fusion, Hyperspectral imaging, Bayes methods, Sun, Signal resolution, neural network framework BibRef

Fan, Z.L.[Zhong-Li], Liu, Y.X.[Yu-Xian], Liu, Y.X.[Yu-Xuan], Zhang, L.[Li], Zhang, J.J.[Jun-Jun], Sun, Y.S.[Yu-Shan], Ai, H.B.[Hai-Bin],
3MRS: An Effective Coarse-to-Fine Matching Method for Multimodal Remote Sensing Imagery,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Dhillon, M.S.[Maninder Singh], Dahms, T.[Thorsten], Kübert-Flock, C.[Carina], Steffan-Dewenter, I.[Ingolf], Zhang, J.[Jie], Ullmann, T.[Tobias],
Spatiotemporal Fusion Modelling Using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Xu, C.[Chuan], Liu, C.[Chang], Li, H.L.[Hong-Li], Ye, Z.W.[Zhi-Wei], Sui, H.G.[Hai-Gang], Yang, W.[Wei],
Multiview Image Matching of Optical Satellite and UAV Based on a Joint Description Neural Network,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Liu, X.Z.[Xiang-Zeng], Xue, J.P.[Jie-Peng], Xu, X.L.[Xue-Ling], Lu, Z.X.[Zi-Xiang], Liu, R.[Ruyi], Zhao, B.C.[Bo-Cheng], Li, Y.[Yunan], Miao, Q.G.[Qi-Guang],
Robust Multimodal Remote Sensing Image Registration Based on Local Statistical Frequency Information,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Khokhlova, M.[Margarita], Abadie, N.[Nathalie], Gouet-Brunet, V.[Valérie], Chen, L.M.[Li-Ming],
GisGCN: A Visual Graph-Based Framework to Match Geographical Areas through Time,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Yan, C.[Chuan], Fan, X.[Xiangsuo], Fan, J.L.[Jin-Long], Wang, N.[Nayi],
Improved U-Net Remote Sensing Classification Algorithm Based on Multi-Feature Fusion Perception,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Swinnen, E.[Else], Sterckx, S.[Sindy], Wirion, C.[Charlotte], Verbeiren, B.[Boud], Wens, D.[Dieter],
Harmonization of Multi-Mission High-Resolution Time Series: Application to BELAIR,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
To get cloud free analysis, data from multiple sensors. BibRef

Yao, Y.X.[Yong-Xiang], Zhang, Y.J.[Yong-Jun], Wan, Y.[Yi], Liu, X.[Xinyi], Yan, X.H.[Xiao-Hu], Li, J.Y.[Jia-Yuan],
Multi-Modal Remote Sensing Image Matching Considering Co-Occurrence Filter,
IP(31), 2022, pp. 2584-2597.
IEEE DOI 2204
Feature extraction, Image matching, Image edge detection, Remote sensing, Matched filters, Nonlinear distortion, log-polar descriptor BibRef

Zhang, Y.J.[Yong-Jun], Yao, Y.X.[Yong-Xiang], Wan, Y.[Yi], Liu, W.Y.[Wei-Yu], Yang, W.[Wupeng], Zheng, Z.[Zhi], Xiao, R.[Rang],
Histogram of the orientation of the weighted phase descriptor for multi-modal remote sensing image matching,
PandRS(196), 2023, pp. 1-15.
Elsevier DOI 2302
Multi-modal remote sensing image, Aggregation feature, Weighted phase orientation feature, Log-polar of regularized, Bidirectional matching BibRef

Ye, Y.X.[Yuan-Xin], Zhu, B.[Bai], Tang, T.F.[Teng-Feng], Yang, C.[Chao], Xu, Q.Z.[Qi-Zhi], Zhang, G.[Guo],
A robust multimodal remote sensing image registration method and system using steerable filters with first- and second-order gradients,
PandRS(188), 2022, pp. 331-350.
Elsevier DOI 2205
Multimodal images, SFOC, Fast-NCC, Integral feature images, Registration system BibRef

Rashwan, S.[Shaheera], Sheta, W.[Walaa],
A Metaheuristics Framework for Weighted Multi-band Image Fusion,
IJIG(22), No. 2, April 2022, pp. 2250016.
DOI Link 2205
BibRef

Fernandes, M.[Michael], Pletl, A.[Alexander], Thomas, N.[Nicolas], Rossi, A.P.[Angelo Pio], Elser, B.[Benedikt],
Generation and Optimization of Spectral Cluster Maps to Enable Data Fusion of CaSSIS and CRISM Datasets,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
Fusion of 2 Mars datasources. Color and Stereo Surface Imaging System. Compact Reconnaissance Imaging Spectrometer. BibRef

Gao, T.[Tong], Chen, H.[Hao], Lu, J.H.[Jun-Hong],
Coupled Heterogeneous Tucker Decomposition: A Feature Extraction Method for Multisource Fusion and Domain Adaptation Using Multisource Heterogeneous Remote Sensing Data,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Zhang, H.W.[Hong-Wei], Huang, F.[Fang], Hong, X.[Xiuchao], Wang, P.[Ping],
A Sensor Bias Correction Method for Reducing the Uncertainty in the Spatiotemporal Fusion of Remote Sensing Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Cheng, F.F.[Fei-Fei], Fu, Z.T.[Zhi-Tao], Tang, B.H.[Bo-Hui], Huang, L.[Liang], Huang, K.[Kun], Ji, X.R.[Xin-Ran],
STF-EGFA: A Remote Sensing Spatiotemporal Fusion Network with Edge-Guided Feature Attention,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
Edge features in fusion operation. BibRef

Li, L.Z.[Liang-Zhi], Han, L.[Ling], Ye, Y.X.[Yuan-Xin],
Self-Supervised Keypoint Detection and Cross-Fusion Matching Networks for Multimodal Remote Sensing Image Registration,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Ul Hoque, M.R.[Md Reshad], Wu, J.[Jian], Kwan, C.[Chiman], Koperski, K.[Krzysztof], Li, J.[Jiang],
ArithFusion: An Arithmetic Deep Model for Temporal Remote Sensing Image Fusion,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Yang, M.C.[Ming-Chuan], Xue, G.C.[Guan-Chang], Liu, B.T.[Bo-Tao], Yang, Y.[Yupu],
Dual Threshold Cooperative Sensing Based Dynamic Spectrum Sharing Algorithm for Integrated Satellite and Terrestrial System,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, L.H.[Long-Hao], Lan, C.Z.[Chao-Zhen], Wu, B.B.[Bei-Bei], Gao, T.[Tian], Wei, Z.J.[Zi-Jun], Yao, F.[Fushan],
A Method for Detecting Feature-Sparse Regions and Matching Enhancement,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Hou, H.[Huitai], Lan, C.Z.[Chao-Zhen], Xu, Q.[Qing], Lv, L.[Liang], Xiong, X.[Xin], Yao, F.[Fushan], Wang, L.H.[Long-Hao],
Attention-Based Matching Approach for Heterogeneous Remote Sensing Images,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Hou, Z.Y.[Zhao-Yang], Lv, K.[Kaiyun], Gong, X.Q.[Xun-Qiang], Wan, Y.T.[Yu-Ting],
A Remote Sensing Image Fusion Method Combining Low-Level Visual Features and Parameter-Adaptive Dual-Channel Pulse-Coupled Neural Network,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Li, H.Q.[Hao-Qing], Duvvuri, B.[Bhavya], Borsoi, R.[Ricardo], Imbiriba, T.[Tales], Beighley, E.[Edward], Erdogmus, D.[Deniz], Closas, P.[Pau],
Online fusion of multi-resolution multispectral images with weakly supervised temporal dynamics,
PandRS(196), 2023, pp. 471-489.
Elsevier DOI 2302
Multimodal image fusion, Online fusion, Bayesian filtering, Water mapping, Super-resolution BibRef

Jha, A.[Ankit], Bose, S.[Shirsha], Banerjee, B.[Biplab],
GAF-Net: Improving the Performance of Remote Sensing Image Fusion using Novel Global Self and Cross Attention Learning,
WACV23(6343-6352)
IEEE DOI 2302
Representation learning, Laser radar, Limiting, Benchmark testing, Feature extraction, Optical imaging, Optical sensors, visual reasoning BibRef

Misra, I.[Indranil], Rohil, M.K.[Mukesh Kumar], Moorthi, S.M.[S. Manthira], Dhar, D.[Debajyoti],
SPRINT: Spectra Preserving Radiance Image Fusion Technique using holistic deep edge spatial attention and Minnaert guided Bayesian probabilistic model,
SP:IC(113), 2023, pp. 116920.
Elsevier DOI 2303
Image fusion, Holistic Nested Edge Detection, Minnaert function, Digital elevation model, Remote sensing BibRef

Bai, S.[Shi], Zhao, J.[Jie],
A New Strategy to Fuse Remote Sensing Data and Geochemical Data with Different Machine Learning Methods,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Liu, H.[Hui], Yang, G.Q.[Guang-Qi], Deng, F.L.[Feng-Liang], Qian, Y.R.[Yu-Rong], Fan, Y.Y.[Ying-Ying],
MCBAM-GAN: The GAN Spatiotemporal Fusion Model Based on Multiscale and CBAM for Remote Sensing Images,
RS(15), No. 6, 2023, pp. 1583.
DOI Link 2304
BibRef

Liu, Z.Q.[Zhi-Qiang], Wang, Z.[Zhao], Zhao, Z.[Zhitao], Huo, L.[Lianzhi], Tang, P.[Ping], Zhang, Z.[Zheng],
Bandpass Alignment from Sentinel-2 to Gaofen-1 ARD Products with UNet-Induced Tile-Adaptive Lookup Tables,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Liang, C.B.[Chen-Bin], Dong, Y.Y.[Yun-Yun], Zhao, C.J.[Chang-Jun], Sun, Z.G.[Zeng-Guo],
A Coarse-to-Fine Feature Match Network Using Transformers for Remote Sensing Image Registration,
RS(15), No. 13, 2023, pp. 3243.
DOI Link 2307
BibRef

Liu, X.Z.[Xiang-Zeng], Xu, X.L.[Xue-Ling], Zhang, X.D.[Xiao-Dong], Miao, Q.G.[Qi-Guang], Wang, L.[Lei], Chang, L.[Liang], Liu, R.[Ruyi],
SRTPN: Scale and Rotation Transform Prediction Net for Multimodal Remote Sensing Image Registration,
RS(15), No. 14, 2023, pp. 3469.
DOI Link 2307
BibRef

Wang, Z.Y.[Zhi-Yuan], Fang, S.[Shuai], Zhang, J.[Jing],
Spatiotemporal Fusion Model of Remote Sensing Images Combining Single-Band and Multi-Band Prediction,
RS(15), No. 20, 2023, pp. 4936.
DOI Link 2310
BibRef

Yang, J.[Jian], Li, C.[Chen], Li, X.L.[Xue-Long],
AA-LMM: Robust Accuracy-Aware Linear Mixture Model for Remote Sensing Image Registration,
RS(15), No. 22, 2023, pp. 5314.
DOI Link 2311
BibRef

Pan, X.Y.[Xiao-Yu], Deng, M.[Muyuan], Ao, Z.[Zurui], Xin, Q.C.[Qin-Chuan],
An Adaptive Multiscale Generative Adversarial Network for the Spatiotemporal Fusion of Landsat and MODIS Data,
RS(15), No. 21, 2023, pp. 5128.
DOI Link 2311
BibRef

Ma, Y.Y.[Yu-Yang], Shen, Y.L.[Yong-Lin], Shen, G.[Guoling], Wang, J.[Jie], Xiao, W.[Wen], He, H.[Huiyang], Hu, C.L.[Chu-Li], Qin, K.[Kai],
STEPSBI: Quick spatiotemporal fusion with coarse- and fine-resolution scale transformation errors and pixel-based synthesis base image pair,
PandRS(206), 2023, pp. 1-15.
Elsevier DOI Code:
WWW Link. 2312
Scale transformation error, Pixel-based synthesized image, Land surface heterogeneity, Google Earth Engine, Spatiotemporal fusion BibRef

Youssef, M.[Mohamed], Bimber, O.[Oliver],
Fusion of Single and Integral Multispectral Aerial Images,
RS(16), No. 4, 2024, pp. 673.
DOI Link 2402
BibRef


Qian, M.[Ming], Xiong, J.C.[Jin-Cheng], Xia, G.S.[Gui-Song], Xue, N.[Nan],
Sat2Density: Faithful Density Learning from Satellite-Ground Image Pairs,
ICCV23(3660-3669)
IEEE DOI 2401
3D using Satellite-Ground pairs BibRef

Yi, J.J.[Jing-Jun], Zhou, B.C.[Bei-Chen],
A Multi-Stage Duplex Fusion Convnet for Aerial Scene Classification,
ICIP22(166-170)
IEEE DOI 2211
Deep learning, Image analysis, Satellites, Semantics, Feature extraction, Real-time systems, Data mining, Duplex Semantic Aggregation BibRef

Tosi, F.[Fabio], Ramirez, P.Z.[Pierluigi Zama], Poggi, M.[Matteo], Salti, S.[Samuele], Mattoccia, S.[Stefano], di Stefano, L.[Luigi],
RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation,
CVPR22(15937-15947)
IEEE DOI 2210
Image resolution, Pipelines, Training data, Sensors, Indoor environment, Synchronization, Self- semi- meta- unsupervised learning BibRef

Lu, J.Y.[Jing-Yang], Yu, C.G.[Cheng-Gang], Blasch, E.[Erik], Ilin, R.[Roman], Chen, H.M.[Hua-Mei], Shen, D.[Dan], Sullivan, N.[Nichole], Chen, G.S.[Gen-She], Kozma, R.[Robert],
Deep Learning Based Domain Adaptation with Data Fusion for Aerial Image Data Analysis,
WAAMI20(118-133).
Springer DOI 2103
BibRef

Liu, G., Chen, Y., Chen, H.,
Remote sensing image registration based on fusion of spatial transformation and dense convolution,
CVIDL20(21-26)
IEEE DOI 2102
convolutional neural nets, feature extraction, geophysical image processing, image fusion, image matching, Remote sensing image registration BibRef

Zhang, H., Fromont, E., Lefevre, S., Avignon, B.,
Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks,
ICIP20(276-280)
IEEE DOI 2011
Training, Feature extraction, Object detection, Fuses, Image segmentation, Semantics, Network architecture, Deep learning BibRef

Farella, E.M., Torresani, A., Remondino, F.,
Quality Features for the Integration of Terrestrial and UAV Images,
3DARCH19(339-346).
DOI Link 1904
BibRef

Yasir, R., Eramian, M., Stavness, I., Shirtliffe, S., Duddu, H.,
Data-Driven Multispectral Image Registration,
CRV18(230-237)
IEEE DOI 1812
Cameras, Image registration, Agriculture, Registers, Image edge detection, Remote sensing, Image registration, Remote sensing BibRef

Zampieri, A.[Armand], Charpiat, G.[Guillaume], Girard, N.[Nicolas], Tarabalka, Y.[Yuliya],
Multimodal Image Alignment Through a Multiscale Chain of Neural Networks with Application to Remote Sensing,
ECCV18(XVI: 679-696).
Springer DOI 1810
BibRef

Ofir, N., Silberstein, S., Levi, H., Rozenbaum, D., Keller, Y., Duvdevani Bar, S.,
Deep Multi-Spectral Registration Using Invariant Descriptor Learning,
ICIP18(1238-1242)
IEEE DOI 1809
Measurement, Image registration, Training, Correlation, Convolution, Corner detection, Deep-Learning, Multi-Spectral Imaging, Image Registration BibRef

Ofir, N., Silberstein, S., Rozenbaum, D., Keller, Y., Bar, S.D.,
Registration and Fusion of Multi-Spectral Images Using a Novel Edge Descriptor,
ICIP18(1857-1861)
IEEE DOI 1809
Image edge detection, Image registration, Image color analysis, Fuses, Gray-scale, Correlation, Image Fusion BibRef

Roy, S., Sangineto, E., Sebe, N., Demir, B.,
Semantic-Fusion GANs for Semi-Supervised Satellite Image Classification,
ICIP18(684-688)
IEEE DOI 1809
Satellites, Training, Semantics, Generators, Generative adversarial networks, Standards, satellite image classification BibRef

Wu, J., Chang, C., Tsai, H.Y., Liu, M.C.,
Co-registration Between Multisource Remote-sensing Images,
ISPRS12(XXXIX-B3:439-442).
DOI Link 1209
BibRef

Zhang, L.B.[Li-Bao], Zhang, J.[Jue],
A new fusion method for remote sensing images based on salient region extraction,
ICIP17(1960-1964)
IEEE DOI 1803
Feature extraction, Geoscience, Handheld computers, Indexes, Principal component analysis, Remote sensing, IHS transform, wavelet transform BibRef

Ma, Y., Liu, D., Mansour, H., Kamilov, U.S., Taguchi, Y., Boufounos, P.T., Vetro, A.,
Fusion of multi-angular aerial images based on epipolar geometry and matrix completion,
ICIP17(1197-1201)
IEEE DOI 1803
Cameras, Geometry, Image fusion, Principal component analysis, Robustness, Spatial resolution, multi-angular BibRef

Feng, R., Li, X., Zou, W., Shen, H.,
Registration of multitemporal GF-1 remote sensing images with weighting perspective transformation model,
ICIP17(2264-2268)
IEEE DOI 1803
geomorphology, geophysical image processing, image registration, remote sensing, AD 2013 04, GaoFen-1, coarse registration, perspective transformation model BibRef

Marcos, D., Hamid, R., Tuia, D.,
Geospatial Correspondences for Multimodal Registration,
CVPR16(5091-5100)
IEEE DOI 1612
BibRef

Zhuo, X., Kurz, F., Reinartz, P.,
Fusion of Multi-View and Multi-Scale Aerial Imagery for Real-Time Situation Awareness Applications,
UAV-g15(201-206).
DOI Link 1512
BibRef

Manu, C.S., Jiji, C.V.,
A novel remote sensing image fusion algorithm using ICA bases,
ICAPR15(1-6)
IEEE DOI 1511
image fusion BibRef

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Gholoum, M., Bruce, D., Al Hazeam, S.,
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Gao, T.[Ting], Xu, Y.[Yu], Xu, T.X.[Ting-Xin],
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Li, L.[Lu], Wang, X.Q.[Xiao-Qin], Li, M.M.[Meng-Meng],
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Jin, B.X.[Bao-Xuan], Li, S.H.[Shi-Hua],
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Ji, L.[Luyan], Jiang, K.[Kang], Geng, X.[Xiurui], Tang, H.R.[Hai-Rong], Yu, K.[Kai], Zhao, Y.C.[Yong-Chao],
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Pei, L.[Liang], Qi, Y.C.[Yuan-Chen], Zhao, H.Y.[Hong-Ying],
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Vodacek, A., Li, Y., Garrett, A.J.,
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Cho, P.,
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IEEE DOI 0710
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Lakshminarayanan, B., Qi, H.R.[Hai-Rong],
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Poland, A.I., Withbroe, G., Evans, J.C.,
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IEEE DOI 0811
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Yang, G.[Gao], Wang, C.[Ci], Tan, Y.P.[Yap-Peng],
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Chen, Y.[Ying], Wang, Y.K.[Ye-Kui], Hannuksela, M.M.[Miska M.], Gabbouj, M.[Moncef],
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Ehlers, M.[Manfred],
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Yao, F.[Fenghui], Sekmen, A.[Ali],
Multi-source Airborne IR and Optical Image Fusion and Its Application to Target Detection,
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Wu, C.C.[Chang-Chang], Fraundorfer, F.[Friedrich], Frahm, J.M.[Jan-Michael], Snoeyink, J.[Jack], Pollefeys, M.[Marc],
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Abedini, A.[Abbas], Hahn, M.[Michael], Samadzadegan, F.[Farhad],
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Wu, H.B.[Hang-Bin], Liu, C.[Chun], Zhou, X.H.[Xin-Hua],
Data Fusion with Integration of Airborne Laser Scanning Data and Ortho-aerial Photos,
ISPRS08(B1: 309 ff).
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Díez, A., Arozarena, A., Ormeño, S., Aguirre, J., Rodríguez, R., Sáenz, A.,
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Schubert, F., Mikolajczyk, K.,
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Mata, F.[Felix],
iRank: Ranking Geographical Information by Conceptual, Geographic and Topologic Similarity,
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Earlier:
Geographic Information Retrieval by Topological, Geographical, and Conceptual Matching,
GS07(98-113).
Springer DOI 0711
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Navarrete, T.[Toni], Blat, J.[Josep],
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Chen, C.F.[Chi-Farn], Chen, M.H.[Min-Hsin], Li, H.T.[Hsiang-Tsu],
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Niranjan, S.[Shobhit], Gupta, G.[Gaurav], Mukerjee, A.[Amitabha], Gupta, S.[Sumana],
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Tomiya, M., Ageishi, A.,
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Kim, H.C.[Hak Chang], Kim, J.H.[Ji Hoon], Lee, S.H.[Sang Hwa], Cho, N.I.[Nam Ik],
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Bustos, J.P., Donoso, F., Guesalaga, A., Torres, M.,
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Yoo, H.Y., Lee, K.,
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Wen, J.T.[Jian-Ting], Li, Y.[Yan], Gong, H.F.[Hai-Feng],
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IEEE DOI 0609
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Beauchemin, M.[Mario], Fung, K.B.[Ko B.], Geng, X.Y.[Xiao-Yuan],
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PCV02(B: 32). 0305
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Zia, A., DeBrunner, V., Chinnaswamy, A., DeBrunner, L.,
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Liedtke, C.E.[Claus-Ebergard], Growe, S.[Stefan],
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Linde, P., Snel, R.,
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SSAB97(Sensors) 9703
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Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Fusion of Hyperspectral Images .


Last update:Mar 16, 2024 at 20:36:19