12.1.4.5 Fusion, Radar Data, SAR Data with Visible Imagery

Wong, R.Y.,
Intensity Signal Processing of Images for Optical to Radar Scene Matching,
ASSP(28), 1980, pp. 260-263. BibRef 8000

Raggam, J., Almer, A., Strobl, D.,
A Combination of SAR and Optical Line Scanner Imagery for Stereoscopic Extraction Of 3-D Data,
PandRS(49), No. 4, August 1994, pp. 11-21. BibRef 9408

Solberg, A.H.S., Jain, A.K.,
Texture Fusion and Feature-Selection Applied to SAR Imagery,
GeoRS(35), No. 2, March 1997, pp. 475-479.
IEEE Top Reference. 9704
BibRef

Wann, C.D., Thomopoulos, S.C.A.,
Application of Self-Organizing Neural Networks to Multiradar Data Fusion,
OptEng(36), No. 3, March 1997, pp. 799-813. 9704
BibRef

Costantini, M., Farina, A., Zirilli, F.,
The Fusion of Different Resolution SAR Images,
PIEEE(85), No. 1, January 1997, pp. 139-146. 9701
BibRef

Le Hegarat-Mascle, S., Bloch, I., Vidal-Madjar, D.,
Introduction of neighborhood information in evidence theory and application to data fusion of radar and optical images with partial cloud cover,
PR(31), No. 11, November 1998, pp. 1811-1823.
Elsevier DOI Spatial information in Demptster-Shafer. BibRef 9811

Crawford, M.M., Kumar, S., Ricard, M.R., Gibeaut, J.C., Neuenschwander, A.,
Fusion of Airborne Polarimetric and Interferometric SAR for Classification of Coastal Environments,
GeoRS(37), No. 3, May 1999, pp. 1306.
IEEE Top Reference. BibRef 9905

Solaiman, B., Pierce, L.E., Ulaby, F.T.,
Multisensor Data Fusion Using Fuzzy Concepts: Application to Land-Cover Classification Using ERS-1/JERS-1 SAR Composites,
GeoRS(37), No. 3, May 1999, pp. 1316.
IEEE Top Reference. BibRef 9905

Haack, B.N.[Barry N.], Herold, N.D.[Nathaniel D.], Bechdol, M.A.[Matthew A.],
Radar and Optical Data Integration for Land-Use/Land-Cover Mapping,
PhEngRS(66), No. 6, June 2000, pp. 709-716. Sensor integration improved the accuracy of mapping land covers 0008
BibRef

Haack, B.N.[Barry N.], Solomon, E.K.[Elizabeth K.], Bechdol, M.A.[Matthew A.], Herold, N.D.[Nathaniel D.],
Radar and Optical Data Comparison/Integration for Urban Delineation: A Case Study,
PhEngRS(68), No. 12, December 2002, pp. 1289-1296. Radar-derived measures such as texture provided better classification accuracies than did optical data.
WWW Link. 0304
BibRef

Dare, P.[Paul], Dowman, I.J.[Ian J.],
An improved model for automatic feature-based registration of SAR and SPOT images,
PandRS(56), No. 1, June 2001, pp. 13-28.
HTML Version. Multiple feature extraction and matching algorithms used. 0108
BibRef

Slatton, K.C., Crawford, M.M., Evans, B.L.,
Fusing interferometric radar and laser altimeter data to estimate surface topography and vegetation heights,
GeoRS(39), No. 11, November 2001, pp. 2470-2482.
IEEE Top Reference. 0111
BibRef

Zhao, H.J.[Hui-Jing], Shibasaki, R.[Ryosuke],
A Robust Method for Registering Ground-Based Laser Range Images of Urban Outdoor Objects,
PhEngRS(67), No. 10, October 2001, pp. 1143-1154.
WWW Link. 0201
Registering multiple ground-based laser range images for the purpose of reconstructing 3D urban outdoor objects, and the efficiency and accuracy is examined through an experiment of registering 42 outdoor laser range images. BibRef

Mills, J.P.[Jon P.], Buckley, S.J.[Simon J.], Mitchell, H.L.[Harvey L.],
Synergistic Fusion of GPS and Photogrammetrically Generated Elevation Models,
PhEngRS(69), No. 4, April 2003, pp. 341-350. Independently collected DEMs derived from kinematic GPS are used to orient surfaces produced by aerial photogrammetric methods by employing a least-squares surface matching algorithm.
WWW Link. 0304
BibRef

Haller, M.C., Lyzenga, D.R.,
Comparison of radar and video observations of shallow water breaking waves,
GeoRS(41), No. 4, April 2003, pp. 832-844.
IEEE Abstract. 0307
BibRef

Lyzenga, D.R., Malinas, N.P., Tanis, F.J.,
Multispectral Bathymetry Using a Simple Physically Based Algorithm,
GeoRS(44), No. 8, August 2006, pp. 2251-2259.
IEEE DOI 0608
BibRef

Onana, V.P., Trouve, E., Mauris, G., Rudant, J.P., Tonye, E.,
Linear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information,
GeoRS(41), No. 11, November 2003, pp. 2540-2556.
IEEE Abstract. 0311
BibRef

Onana, V.P., Trouvé, E., Mauris, G., Rudant, J.P., Tonyé, E.,
Detection of Linear Features in Synthetic-Aperture Radar Images by use of the Localized Radon Transform and Prior Information,
AppOpt(43), No. 2, 2004, pp. 264-273.
WWW Link. BibRef 0400

Hill, M.J., Ticehurst, C.J., Lee, J.S., Grunes, M.R., Donald, G.E., Henry, D.,
Integration of Optical and Radar Classifications for Mapping Pasture Type in Western Australia,
GeoRS(43), No. 7, July 2005, pp. 1665-1681.
IEEE DOI 0508
BibRef

Hong, T.D.[Tai D.], Schowengerdt, R.A.[Robert A.],
A Robust Technique for Precise Registration of Radar and Optical Satellite Images,
PhEngRS(71), No. 5, May 2005, pp. 585-594. A new method for automatically registering two dissimilar images, such as, a radar image and a optical image with high accuracy.
WWW Link. 0509
BibRef

Chibani, Y.[Youcef],
Selective Synthetic Aperture Radar and Panchromatic Image Fusion by Using the a Trous Wavelet Decomposition,
JASP(2005), No. 14, 2005, pp. 2207-2214.
WWW Link. 0603
BibRef

Chibani, Y.[Youcef],
Additive integration of SAR features into multispectral SPOT images by means of the à trous wavelet decomposition,
PandRS(60), No. 5, August 2006, pp. 306-314.
Elsevier DOI 0610
Intensity-hue-saturation transform; Modified Brovey transform; a trous wavelet decomposition; Remote sensing BibRef

Hong, G.[Gang], Zhang, Y.[Yun], Mercer, B.[Bryan],
A Wavelet and IHS Integration Method to Fuse High Resolution SAR with Moderate Resolution Multispectral Images,
PhEngRS(75), No. 10, October 2009, pp. 1213-1224.
WWW Link. 0910
Successful results are achieved in the fusion of all SAR and MS images from a variety of sensors with significant spatial and spectral variations using the proposed image fusion method. BibRef

McNairn, H.[Heather], Champagne, C.[Catherine], Shang, J.L.[Jia-Li], Holmstrom, D.[Delmar], Reichert, G.[Gordon],
Integration of optical and Synthetic Aperture Radar (SAR) imagery for delivering operational annual crop inventories,
PandRS(64), No. 5, September 2009, pp. 434-449.
Elsevier DOI 0910
Crops; Classification; SAR; Optical; Multi-polarization BibRef

Nitti, D.O., Hanssen, R.F., Refice, A., Bovenga, F., Nutricato, R.,
Impact of DEM-Assisted Coregistration on High-Resolution SAR Interferometry,
GeoRS(49), No. 3, March 2011, pp. 1127-1143.
IEEE DOI 1103

See also Corrections to Impact of DEM-Assisted Coregistration on High-Resolution SAR Interferometry. BibRef

Li, D., Zhang, Y.,
Corrections to 'Impact of DEM-Assisted Coregistration on High-Resolution SAR Interferometry',
GeoRS(49), No. 11, November 2011, pp. 4677.
IEEE DOI 1112

See also Impact of DEM-Assisted Coregistration on High-Resolution SAR Interferometry. BibRef

Catalan, P.A., Haller, M.C., Holman, R.A., Plant, W.J.,
Optical and Microwave Detection of Wave Breaking in the Surf Zone,
GeoRS(49), No. 6, June 2011, pp. 1879-1893.
IEEE DOI 1106
BibRef

Catalao, J., Nico, G., Hanssen, R., Catita, C.,
Merging GPS and Atmospherically Corrected InSAR Data to Map 3-D Terrain Displacement Velocity,
GeoRS(49), No. 6, June 2011, pp. 2354-2360.
IEEE DOI 1106
BibRef

Ji, Z., Luciw, M., Weng, J., Zeng, S.,
Incremental Online Object Learning in a Vehicular Radar-Vision Fusion Framework,
ITS(12), No. 2, June 2011, pp. 402-411.
IEEE DOI 1101
BibRef

Xueyun, W., Huaping, X., Jingwen, L., Pengbo, W.,
Comparison of diverse approaches for synthetic aperture radar images pixel fusion under different precision registration,
IET-IPR(5), No. 8, 2011, pp. 661-670.
DOI Link 1108
BibRef

Quin, G., Loreaux, P.,
Submillimeter Accuracy of Multipass Corner Reflector Monitoring by PS Technique,
GeoRS(51), No. 3, March 2013, pp. 1775-1783.
IEEE DOI 1303
BibRef

Ceccherini, G.[Guido], Gobron, N.[Nadine], Robustelli, M.[Monica],
Harmonization of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from Sea-ViewingWide Field-of-View Sensor (SeaWiFS) and Medium Resolution Imaging Spectrometer Instrument (MERIS),
RS(5), No. 7, 2013, pp. 3357-3376.
DOI Link 1308
BibRef

Schmitt, M.[Michael], Maksymiuk, O.[Oliver], Magnard, C.[Christophe], Stilla, U.[Uwe],
Radargrammetric registration of airborne multi-aspect SAR data of urban areas,
PandRS(86), No. 1, 2013, pp. 11-20.
Elsevier DOI 1312
Synthetic Aperture Radar (SAR) BibRef

Schmitt, M.[Michael], Stilla, U.[Uwe],
Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas,
PandRS(87), No. 1, 2014, pp. 68-77.
Elsevier DOI 1402
Synthetic Aperture Radar (SAR) BibRef

Castaneda, V.[Victor], Mateus, D.[Diana], Navab, N.[Nassir],
Stereo Time-of-Flight with Constructive Interference,
PAMI(36), No. 7, July 2014, pp. 1402-1413.
IEEE DOI 1407
BibRef
Earlier:
Stereo time-of-flight,
ICCV11(1684-1691).
IEEE DOI 1201
BibRef
And:
SLAM combining ToF and high-resolution cameras,
WMVC11(672-678).
IEEE DOI 1101
Biomedical measurement. Actively modify the IR lighting for 2 cameras, combine measurements at low level BibRef

Sui, H.G.[Hai-Gang], Xu, C.[Chuan], Liu, J.[Junyi], Hua, F.[Feng],
Automatic Optical-to-SAR Image Registration by Iterative Line Extraction and Voronoi Integrated Spectral Point Matching,
GeoRS(53), No. 11, November 2015, pp. 6058-6072.
IEEE DOI 1509
feature extraction BibRef

Garzelli, A.[Andrea],
A Review of Image Fusion Algorithms Based on the Super-Resolution Paradigm,
RS(8), No. 10, 2016, pp. 797.
DOI Link 1609
Survey, Fusion. BibRef

Garzelli, A.[Andrea],
Wavelet-Based Fusion of Optical and SAR Image Data over Urban Area,
PCV02(B: 59). 0305
BibRef

Rui, J.[Jie], Wang, C.[Chao], Zhang, H.[Hong], Jin, F.[Fei],
Multi-Sensor SAR Image Registration Based on Object Shape,
RS(8), No. 11, 2016, pp. 923.
DOI Link 1612
BibRef

Salehpour, M.[Mehdi], Behrad, A.[Alireza],
Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network,
JOSA-A(34), No. 10, October 2017, pp. 1865-1876.
DOI Link 1710
Image analysis, Synthetic aperture radar, Multispectral and hyperspectral imaging, Remote sensing and sensors BibRef

Chen, M.[Min], Habib, A.[Ayman], He, H.Q.[Hai-Qing], Zhu, Q.[Qing], Zhang, W.[Wei],
Robust Feature Matching Method for SAR and Optical Images by Using Gaussian-Gamma-Shaped Bi-Windows-Based Descriptor and Geometric Constraint,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Zhai, A.[Aobo], Wen, X.B.[Xian-Bin], Xu, H.X.[Hai-Xia], Yuan, L.M.[Li-Ming], Meng, Q.X.[Qing-Xia],
Multi-Layer Model Based on Multi-Scale and Multi-Feature Fusion for SAR Images,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Yang, X., Wang, J., Zhu, R.,
Random Walks for Synthetic Aperture Radar Image Fusion in Framelet Domain,
IP(27), No. 2, February 2018, pp. 851-865.
IEEE DOI 1712
Fuses, Image edge detection, Image fusion, Probability, Synthetic aperture radar, Wavelet transforms, Image fusion, visible image BibRef

Wang, J.P.[Jian-Ping], Aubry, P.[Pascal], Yarovoy, A.[Alexander],
Wavenumber-Domain Multiband Signal Fusion With Matrix-Pencil Approach for High-Resolution Imaging,
GeoRS(56), No. 7, July 2018, pp. 4037-4049.
IEEE DOI 1807
Antenna arrays, Bandwidth, Microwave imaging, Radar imaging, Scattering, Matrix-pencil approach (MPA), microwave imaging, wavenumber domain BibRef

Fan, J., Wu, Y., Li, M., Liang, W., Cao, Y.,
SAR and Optical Image Registration Using Nonlinear Diffusion and Phase Congruency Structural Descriptor,
GeoRS(56), No. 9, September 2018, pp. 5368-5379.
IEEE DOI 1809
Feature extraction, Nonlinear optics, Optical imaging, Synthetic aperture radar, Optical sensors, Adaptive optics, synthetic aperture radar (SAR) and optical images BibRef

Seo, D.K.[Dae Kyo], Kim, Y.H.[Yong Hyun], Eo, Y.D.[Yang Dam], Lee, M.H.[Mi Hee], Park, W.Y.[Wan Yong],
Fusion of SAR and Multispectral Images Using Random Forest Regression for Change Detection,
IJGI(7), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Hughes, L.H.[Lloyd Haydn], Schmitt, M.[Michael], Zhu, X.X.[Xiao Xiang],
Mining Hard Negative Samples for SAR-Optical Image Matching Using Generative Adversarial Networks,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

He, C.[Chu], Fang, P.Z.[Pei-Zhang], Xiong, D.H.[De-Hui], Wang, W.W.[Wen-Wei], Liao, M.S.[Ming-Sheng],
A Point Pattern Chamfer Registration of Optical and SAR Images Based on Mesh Grids,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Hu, J.L.[Jing-Liang], Hong, D.F.[Dan-Feng], Wang, Y.Y.[Yuan-Yuan], Zhu, X.X.[Xiao Xiang],
A Comparative Review of Manifold Learning Techniques for Hyperspectral and Polarimetric SAR Image Fusion,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Lekic, V.[Vladimir], Babic, Z.[Zdenka],
Automotive radar and camera fusion using Generative Adversarial Networks,
CVIU(184), 2019, pp. 1-8.
Elsevier DOI 1906
Radar, Camera, Unsupervised learning, Generative Adversarial Networks, Driver assistance BibRef

Xiang, Y., Wang, F., Wan, L., Jiao, N., You, H.,
OS-Flow: A Robust Algorithm for Dense Optical and SAR Image Registration,
GeoRS(57), No. 9, September 2019, pp. 6335-6354.
IEEE DOI 1909
Optical imaging, Optical sensors, Adaptive optics, Radar polarimetry, Nonlinear optics, Remote sensing, synthetic aperture radar (SAR) BibRef

He, G.X.[Guang-Xin], Sun, J.Z.[Juan-Zhen], Ying, Z.M.[Zhu-Ming], Zhang, L.J.[Le-Jian],
A Radar Radial Velocity Dealiasing Algorithm for Radar Data Assimilation and its Evaluation with Observations from Multiple Radar Networks,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Hu, J., Hong, D., Zhu, X.X.,
MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data,
GeoRS(57), No. 11, November 2019, pp. 9025-9040.
IEEE DOI 1911
Optical imaging, Optical sensors, Synthetic aperture radar, Remote sensing, Optical distortion, Manifolds, Optical scattering, topological data analysis (TDA) BibRef

Wang, Z.[Zheng], Li, Z.H.[Zhen-Hong], Mills, J.[Jon],
Modelling of instrument repositioning errors in discontinuous Multi-Campaign Ground-Based SAR (MC-GBSAR) deformation monitoring,
PandRS(157), 2019, pp. 26-40.
Elsevier DOI 1911
Ground-Based SAR (GBSAR), Interferometry, Multi-campaign, Repositioning errors, Correction, Deformation monitoring BibRef

Bürgmann, T.[Tatjana], Koppe, W.[Wolfgang], Schmitt, M.[Michael],
Matching of TerraSAR-X derived ground control points to optical image patches using deep learning,
PandRS(158), 2019, pp. 241-248.
Elsevier DOI 1912
GCP matching, Multi-sensor image matching, Deep learning, Synthetic aperture radar, Optical satellite images, Geolocation accuracy improvement BibRef

Paul, S.[Sourabh], Pati, U.C.[Umesh C.],
Automatic optical-to-SAR image registration using a structural descriptor,
IET-IPR(14), No. 1, January 2020, pp. 62-73.
DOI Link 1912
BibRef

Zhou, Y., Zhang, L., Cao, Y., Huang, Y.,
Optical-and-Radar Image Fusion for Dynamic Estimation of Spin Satellites,
IP(29), 2020, pp. 2963-2976.
IEEE DOI 2002
Satellites, Optical imaging, Radar imaging, Optical sensors, Spaceborne radar, Estimation, Dynamic estimation, spin satellites, image interpretation BibRef

Zhu, Q.S.[Quan-Sheng], Jiang, W.[Wanshou], Zhu, Y.[Ying], Li, L.[Linze],
Geometric Accuracy Improvement Method for High-Resolution Optical Satellite Remote Sensing Imagery Combining Multi-Temporal SAR Imagery and GLAS Data,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Ahmad, S.K., Hossain, F., Eldardiry, H., Pavelsky, T.M.,
A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions,
GeoRS(58), No. 4, April 2020, pp. 2471-2480.
IEEE DOI 2004
Area classification, remote sensing, synthetic aperture radar (SAR), visible imagery, water bodies BibRef

Xiang, Y., Tao, R., Wan, L., Wang, F., You, H.,
OS-PC: Combining Feature Representation and 3-D Phase Correlation for Subpixel Optical and SAR Image Registration,
GeoRS(58), No. 9, September 2020, pp. 6451-6466.
IEEE DOI 2008
Optical sensors, Optical imaging, Synthetic aperture radar, Robustness, Correlation, Adaptive optics, Image registration, subpixel BibRef

Shao, Z.F.[Zhen-Feng], Wu, W.[Wenfu], Guo, S.J.[Song-Jing],
IHS-GTF: A Fusion Method for Optical and Synthetic Aperture Radar Data,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Wang, L.[Lina], Sun, M.C.[Ming-Chao], Liu, J.H.[Jing-Hong], Cao, L.H.[Li-Hua], Ma, G.Q.[Guo-Qing],
A Robust Algorithm Based on Phase Congruency for Optical and SAR Image Registration in Suburban Areas,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Hughes, L.H.[Lloyd Haydn], Marcos, D.[Diego], Lobry, S.[Sylvain], Tuia, D.[Devis], Schmitt, M.[Michael],
A deep learning framework for matching of SAR and optical imagery,
PandRS(169), 2020, pp. 166-179.
Elsevier DOI 2011
Multi-modal image matching, Image registration, Feature detection, Deep learning, Optical imagery BibRef

Yu, Q.[Qiuze], Ni, D.[Dawen], Jiang, Y.X.[Yu-Xuan], Yan, Y.X.[Yu-Xuan], An, J.[Jiachun], Sun, T.[Tao],
Universal SAR and optical image registration via a novel SIFT framework based on nonlinear diffusion and a polar spatial-frequency descriptor,
PandRS(171), 2021, pp. 1-17.
Elsevier DOI 2012
Synthetic aperture radar (SAR) image, Nonlinear diffusion, Consistent gradient, Log-Gabor response, Image registration BibRef

Rodger, M.[Maximilian], Guida, R.[Raffaella],
Classification-Aided SAR and AIS Data Fusion for Space-Based Maritime Surveillance,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
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Zheng, Z.[Zhuo], Ma, A.L.[Ai-Long], Zhang, L.P.[Liang-Pei], Zhong, Y.F.[Yan-Fei],
Deep multisensor learning for missing-modality all-weather mapping,
PandRS(174), 2021, pp. 254-264.
Elsevier DOI 2103
SAR and optical. Use historical data to improve results. Multi-sensor, Deep learning, Missing-modality, All-weather mapping, Optical imagery, Remote sensing BibRef

Ye, Y.X.[Yuan-Xin], Yang, C.[Chao], Zhu, B.[Bai], Zhou, L.[Liang], He, Y.Q.[You-Quan], Jia, H.R.[Hua-Rong],
Improving Co-Registration for Sentinel-1 SAR and Sentinel-2 Optical Images,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
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Wang, Z.J.[Zhang-Jing], Miao, X.H.[Xian-Han], Huang, Z.[Zhen], Luo, H.R.[Hao-Ran],
Research of Target Detection and Classification Techniques Using Millimeter-Wave Radar and Vision Sensors,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Kong, Y.Y.[Ying-Ying], Yan, B.Y.[Bi-Yuan], Liu, Y.J.[Yan-Juan], Leung, H.[Henry], Peng, X.Y.[Xiang-Yang],
Feature-Level Fusion of Polarized SAR and Optical Images Based on Random Forest and Conditional Random Fields,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Paul, S.[Sourabh], Pati, U.C.[Umesh C.],
High-resolution optical-to-SAR image registration using mutual information and SPSA optimisation,
IET-IPR(15), No. 6, 2021, pp. 1319-1331.
DOI Link 2106
BibRef

Eibedingil, I.G.[Iyasu G.], Gill, T.E.[Thomas E.], van Pelt, R.S.[R. Scott], Tong, D.Q.[Daniel Q.],
Combining Optical and Radar Satellite Imagery to Investigate the Surface Properties and Evolution of the Lordsburg Playa, New Mexico, USA,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Fan, Z.L.[Zhong-Li], Zhang, L.[Li], Liu, Y.X.[Yu-Xuan], Wang, Q.D.[Qing-Dong], Zlatanova, S.[Sisi],
Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Jiao, R.Z.[Run-Zhi], Wang, Q.S.[Qing-Song], Lai, T.[Tao], Huang, H.F.[Hai-Feng],
Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Kong, Y.Y.[Ying-Ying], Hong, F.[Fang], Leung, H.[Henry], Peng, X.Y.[Xiang-Yang],
A Fusion Method of Optical Image and SAR Image Based on Dense-UGAN and Gram-Schmidt Transformation,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
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Guo, L.[Liang],
SAR image classification based on multi-feature fusion decision convolutional neural network,
IET-IPR(16), No. 1, 2022, pp. 1-10.
DOI Link 2112
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Li, S.[Shuo], Lv, X.L.[Xiao-Lei], Ren, J.[Jian], Li, J.[Jian],
A Robust 3D Density Descriptor Based on Histogram of Oriented Primary Edge Structure for SAR and Optical Image Co-Registration,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Fan, F.[Fan], Zeng, X.F.[Xiang-Feng], Wei, S.J.[Shun-Jun], Zhang, H.[Hao], Tang, D.[Dianhua], Shi, J.[Jun], Zhang, X.L.[Xiao-Ling],
Efficient Instance Segmentation Paradigm for Interpreting SAR and Optical Images,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhang, H.[Hai], Shen, H.[Huanfeng], Yuan, Q.Q.[Qiang-Qiang], Guan, X.B.[Xia-Bin],
Multispectral and SAR Image Fusion Based on Laplacian Pyramid and Sparse Representation,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Fan, Y.[Yibo], Wang, F.[Feng], Wang, H.P.[Hai-Peng],
A Transformer-Based Coarse-to-Fine Wide-Swath SAR Image Registration Method under Weak Texture Conditions,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Zhu, J.B.[Jin-Biao], Pan, J.[Jie], Jiang, W.[Wen], Yue, X.J.[Xi-Juan], Yin, P.Y.[Peng-Yu],
SAR Image Fusion Classification Based on the Decision-Level Combination of Multi-Band Information,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Nie, H.[Han], Fu, Z.T.[Zhi-Tao], Tang, B.H.[Bo-Hui], Li, Z.Q.[Zi-Qian], Chen, S.J.[Si-Jing], Wang, L.G.[Lei-Guang],
A Dual-Generator Translation Network Fusing Texture and Structure Features for SAR and Optical Image Matching,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Qian, L.X.[Li-Xin], Liu, X.C.[Xiao-Chun], Huang, M.[Meiyu], Xiang, X.S.[Xue-Shuang],
Self-Supervised Pre-Training with Bridge Neural Network for SAR-Optical Matching,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Xiao, X.[Xiao], Li, C.J.[Chang-Jian], Lei, Y.J.[Yin-Jie],
A Lightweight Self-Supervised Representation Learning Algorithm for Scene Classification in Spaceborne SAR and Optical Images,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Li, X.C.[Xin-Chen], Jing, D.[Dan], Li, Y.[Yachao], Guo, L.[Liang], Han, L.[Liang], Xu, Q.[Qing], Xing, M.D.[Meng-Dao], Hu, Y.H.[Yi-Hua],
Multi-Band and Polarization SAR Images Colorization Fusion,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Xie, Z.K.[Zhi-Kun], Shi, J.[Jun], Zhou, Y.H.[Yi-Hang], Yang, X.Q.[Xia-Qing], Guo, W.X.[Wen-Xuan], Zhang, X.L.[Xiao-Ling],
S2-PCM: Super-Resolution Structural Point Cloud Matching for High-Accuracy Video-SAR Image Registration,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Wang, Z.B.[Zheng-Bin], Yu, A.X.[An-Xi], Zhang, B.[Ben], Dong, Z.[Zhen], Chen, X.[Xing],
A Fast Registration Method for Optical and SAR Images Based on SRAWG Feature Description,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Shakya, A.[Achala], Biswas, M.[Mantosh], Pal, M.[Mahesh],
Fusion and Classification of SAR and Optical Data Using Multi-Image Color Components with Differential Gradients,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

He, G.J.[Guang-Jun], Dong, Z.[Zhe], Guan, J.[Jian], Feng, P.M.[Peng-Ming], Jin, S.C.[Shi-Chao], Zhang, X.L.[Xue-Liang],
SAR and Multi-Spectral Data Fusion for Local Climate Zone Classification with Multi-Branch Convolutional Neural Network,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
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Sommervold, O.[Oscar], Gazzea, M.[Michele], Arghandeh, R.[Reza],
A Survey on SAR and Optical Satellite Image Registration,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Desage, L.[Léopold], Herique, A.[Alain], Douté, S.[Sylvain], Zine, S.[Sonia], Kofman, W.[Wlodek],
Resolving Ambiguities in SHARAD Data Analysis Using High-Resolution Digital Terrain Models,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
SHAllow RADar (SHARAD) onboard Mars Reconnaissance Orbiter (MRO). BibRef

Gomes-Duarte-di Toro, A.P.S.[Ana Paola Salas], Bueno, I.T.[Inacio T.], Werner, J.P.S.[João P. S.], Antunes, J.F.G.[João F. G.], Lamparelli, R.A.C.[Rubens A. C.], Coutinho, A.C.[Alexandre C.], Mora-Esquerdo, J.C.D.[Júlio Cesar Dalla], Magalhães, P.S.G.[Paulo S. G.], Araújo-Figueiredo, G.K.D.[Gleyce Kelly Dantas],
SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Li, W.B.[Wang-Bin], Sun, K.[Kaimin], Li, W.Z.[Wen-Zhuo], Wei, J.J.[Jin-Jiang], Miao, S.X.[Shun-Xia], Gao, S.[Song], Zhou, Q.H.[Qin-Hui],
Aligning semantic distribution in fusing optical and SAR images for land use classification,
PandRS(199), 2023, pp. 272-288.
Elsevier DOI 2305
Land use classification, Spatial-aware circular module, Semantic distribution alignment loss, Fusion condition BibRef

Zhang, J.J.[Jia-Jia], Li, H.[Huan], Zhao, D.[Dong], Arun, P.V.[Pattathal V.], Tan, W.[Wei], Xiang, P.[Pei], Zhou, H.X.[Hui-Xin], Hu, J.L.[Jian-Ling], Du, J.[Juan],
An ISAR and Visible Image Fusion Algorithm Based on Adaptive Guided Multi-Layer Side Window Box Filter Decomposition,
RS(15), No. 11, 2023, pp. 2784.
DOI Link 2306
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Luo, J.H.[Jia-Hao], Zhou, F.[Fang], Yang, J.[Jun], Xing, M.D.[Meng-Dao],
DAFCNN: A Dual-Channel Feature Extraction and Attention Feature Fusion Convolution Neural Network for SAR Image and MS Image Fusion,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
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Hu, C.B.[Can-Bin], Zhu, R.[Runze], Sun, X.K.[Xiao-Kun], Li, X.W.[Xin-Wei], Xiang, D.L.[De-Liang],
Optical and SAR Image Registration Based on Pseudo-SAR Image Generation Strategy,
RS(15), No. 14, 2023, pp. 3528.
DOI Link 2307
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Chen, J.X.[Jia-Xing], Xie, H.[Hongtu], Zhang, L.[Lin], Hu, J.[Jun], Jiang, H.[Hejun], Wang, G.Q.[Guo-Qian],
SAR and Optical Image Registration Based on Deep Learning with Co-Attention Matching Module,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Liu, Y.H.[Yi-Heng], Zhang, H.[Hua], Wang, X.M.[Xue-Mei], Dong, Q.H.[Qing-Hai], Lyu, X.[Xiaode],
An Improved Multi-Frame Coherent Integration Algorithm for Heterogeneous Radar,
RS(15), No. 16, 2023, pp. 4026.
DOI Link 2309
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He, W.[Wei], Deng, Z.[Zhenmiao], Ye, Y.S.[Yi-Shan], Pan, P.P.[Ping-Ping],
ConCs-Fusion: A Context Clustering-Based Radar and Camera Fusion for Three-Dimensional Object Detection,
RS(15), No. 21, 2023, pp. 5130.
DOI Link 2311
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Li, J.J.[Jin-Jin], Zhang, J.C.[Jia-Cheng], Yang, C.[Chao], Liu, H.Y.[Hui-Yu], Zhao, Y.G.[Yan-Gang], Ye, Y.Y.X.[Yuan-Yan-Xin],
Comparative Analysis of Pixel-Level Fusion Algorithms and a New High-Resolution Dataset for SAR and Optical Image Fusion,
RS(15), No. 23, 2023, pp. 5514.
DOI Link 2312
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Deng, J.Y.[Jia-Yin], Hu, Z.Q.[Zhi-Qun], Lu, Z.M.[Zhao-Ming], Wen, X.M.[Xiang-Ming],
FusionCalib: Automatic extrinsic parameters calibration based on road plane reconstruction for roadside integrated radar camera fusion sensors,
PRL(176), 2023, pp. 7-13.
Elsevier DOI 2312
Radar camera fusion, Roadside sensor, Road plane reconstruction, Extrinsic parameters calibration BibRef

Li, Y.[Yang], Cui, X.[Xiwei], Wang, Y.P.[Yan-Ping], Sun, J.P.[Jin-Ping],
Correlative Scan Matching Position Estimation Method by Fusing Visual and Radar Line Features,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
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Yang, L.[Lihe], Feng, W.[Wei], Wu, Y.J.[Yao-Jun], Huang, L.[Liang], Quan, Y.H.[Ying-Hui],
Radar-Infrared Sensor Fusion Based on Hierarchical Features Mining,
SPLetters(31), 2024, pp. 66-70.
IEEE DOI 2401
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Shao, Z.F.[Zhen-Feng], Ahmad, M.N.[Muhammad Nasar], Javed, A.[Akib],
Comparison of Random Forest and XGBoost Classifiers Using Integrated Optical and SAR Features for Mapping Urban Impervious Surface,
RS(16), No. 4, 2024, pp. 665.
DOI Link 2402
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Ahmad, M.N.[Muhammad Nasar], Shao, Z.F.[Zhen-Feng], Javed, A.[Akib], Ahmad, I.[Israr], Islam, F.[Fakhrul], Skilodimou, H.D.[Hariklia D.], Bathrellos, G.D.[George D.],
Optical-SAR Data Fusion Based on Simple Layer Stacking and the XGBoost Algorithm to Extract Urban Impervious Surfaces in Global Alpha Cities,
RS(16), No. 5, 2024, pp. 873.
DOI Link 2403
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Luo, C.[Cheng], Zhang, Y.T.[Yue-Ting], Guo, J.Y.[Jia-Yi], Hu, Y.X.[Yu-Xin], Zhou, G.Y.[Guang-Yao], You, H.J.[Hong-Jian], Ning, X.[Xia],
SAR-CDSS: A Semi-Supervised Cross-Domain Object Detection from Optical to SAR Domain,
RS(16), No. 6, 2024, pp. 940.
DOI Link 2403
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Xu, D.D.[Dong-Dong], Li, Z.[Zheng], Feng, H.[Hao], Wu, F.[Fanlu], Wang, Y.C.[Yong-Cheng],
Multi-Scale Feature Fusion Network with Symmetric Attention for Land Cover Classification Using SAR and Optical Images,
RS(16), No. 6, 2024, pp. 957.
DOI Link 2403
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Guo, F.Q.[Feng-Qi], Zhu, J.P.[Jing-Ping], Huang, L.Q.[Li-Qing], Li, F.[Feng], Zhang, N.[Ning], Deng, J.X.[Jin-Xin], Li, H.X.[Hao-Xiang], Zhang, X.Z.[Xiang-Zhe], Zhao, Y.C.[Yuan-Chen], Jiang, H.L.[Hui-Lin], Hou, X.[Xun],
Multi-Dimensional Fusion of Spectral and Polarimetric Images Followed by Pseudo-Color Algorithm Integration and Mapping in HSI Space,
RS(16), No. 7, 2024, pp. 1119.
DOI Link 2404
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Feng, L.[Luwei], Gui, D.W.[Da-Wei], Han, S.S.[Shan-Shan], Qiu, T.Q.[Tian-Qi], Wang, Y.[Yumiao],
Integrating Optical and SAR Time Series Images for Unsupervised Domain Adaptive Crop Mapping,
RS(16), No. 8, 2024, pp. 1464.
DOI Link 2405
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Kluczek, M.[Marcin], Zagajewski, B.[Bogdan], Kycko, M.[Marlena],
Combining Multitemporal Optical and Radar Satellite Data for Mapping the Tatra Mountains Non-Forest Plant Communities,
RS(16), No. 8, 2024, pp. 1451.
DOI Link 2405
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Hu, W.[Wei], Wang, X.H.[Xin-Hui], Zhan, F.[Feng], Cao, L.[Lu], Liu, Y.[Yong], Yang, W.[Weili], Ji, M.J.[Ming-Jiang], Meng, L.[Ling], Guo, P.Y.[Peng-Yu], Yang, Z.[Zhi], Liu, Y.H.[Yu-Hang],
OPT-SAR-MS2Net: A Multi-Source Multi-Scale Siamese Network for Land Object Classification Using Remote Sensing Images,
RS(16), No. 11, 2024, pp. 1850.
DOI Link 2406
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Yang, Y.Q.[Yan-Qiu], Wang, X.[Xianpeng], Wu, X.Q.[Xiao-Qin], Lan, X.[Xiang], Su, T.[Ting], Guo, Y.[Yuehao],
A Robust Target Detection Algorithm Based on the Fusion of Frequency-Modulated Continuous Wave Radar and a Monocular Camera,
RS(16), No. 12, 2024, pp. 2225.
DOI Link 2406
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Santos, A.R.[Allita R.], Barbosa, M.A.G.A.[Mariana A. G. A.], Anjinho, P.S.[Phelipe S.], Parizotto, D.[Denise], Mauad, F.F.[Frederico F.],
Integrated Use of Synthetic Aperture Radar and Optical Data in Mapping Native Vegetation: A Study in a Transitional Brazilian Cerrado-Atlantic Forest Interface,
RS(16), No. 14, 2024, pp. 2559.
DOI Link 2408
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Zhang, K.[Keke], Yu, A.X.[An-Xi], Tong, W.H.[Wen-Hao], Dong, Z.[Zhen],
A Robust SAR-Optical Heterologous Image Registration Method Based on Region-Adaptive Keypoint Selection,
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Kakooei, M.[Mohammad], Baleghi, Y.[Yasser],
Mapping Building Heights at Large Scales Using Sentinel-1 Radar Imagery and Nighttime Light Data,
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Li, S.L.[Sheng-Lei], Luo, H.R.[Hao-Ran], Shao, T.F.[Teng-Fei], Hishiyama, R.[Reiko],
A mmWave Sensor and Camera Fusion System for Indoor Occupancy Detection and Tracking,
IEICE(E108-D), No. 9, September 2024, pp. 1192-1205.
WWW Link. 2410
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Yang, Y.Q.[Yan-Qiu], Wang, X.P.[Xian-Peng], Wu, X.Q.[Xiao-Qin], Lan, X.[Xiang], Su, T.[Ting], Guo, Y.H.[Yue-Hao],
A Target Detection Algorithm Based on Fusing Radar with a Camera in the Presence of a Fluctuating Signal Intensity,
RS(16), No. 18, 2024, pp. 3356.
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Zhao, L.Z.[Li-Zhi], Wang, J.L.[Jun-Ling], Su, J.[Jiaoyang], Luo, H.Y.[Hao-Yue],
Spatial Feature-Based ISAR Image Registration for Space Targets,
RS(16), No. 19, 2024, pp. 3625.
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Li, H.[Han], Ma, Y.[Yukai], Huang, Y.[Yuehao], Gu, Y.Q.[Ya-Qing], Xu, W.H.[Wei-Hua], Liu, Y.[Yong], Zuo, X.X.[Xing-Xing],
RIDERS: Radar-Infrared Depth Estimation for Robust Sensing,
ITS(25), No. 11, November 2024, pp. 18764-18778.
IEEE DOI Code:
WWW Link. 2411
Radar, Radar imaging, Estimation, Cameras, Measurement, Laser radar, Accuracy, Depth estimation, radar perception, infrared camera, multi-sensor fusion BibRef

Sánchez-Fernández, J.[Jaime], Fernández-Landa, A.[Alfredo], Cabezudo, Á.H.[Álvaro Hernández], Sánchez, R.M.[Rafael Molina],
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Zhang, P.[Pan], Peng, B.C.[Bao-Chai], Lu, C.R.[Chao-Ran], Huang, Q.J.[Quan-Jin], Liu, D.S.[Dong-Sheng],
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PandRS(218), 2024, pp. 574-587.
Elsevier DOI 2412
Land cover classification, Multimodal, Semantic segmentation, Feature interaction BibRef

Fan, X.Y.[Xin-Yue], Zhang, L.B.[Li-Bao],
Land Use Classification Via Multi-Modal Complementary Feature Fusion and Context Information Enhancement for Optical and SAR Images,
ICIP24(2669-2675)
IEEE DOI 2411
Integrated optics, Convolution, Semantics, Optical fiber networks, Optical imaging, Feature extraction, Radar polarimetry, land use classification BibRef

Zhao, L.J.[Ling-Jun], Song, J.Y.[Jing-Yu], Skinner, K.A.[Katherine A.],
CRKD: Enhanced Camera-Radar Object Detection with Cross-Modality Knowledge Distillation,
CVPR24(15470-15480)
IEEE DOI Code:
WWW Link. 2410
Laser radar, Costs, Roads, Object detection, Detectors BibRef

Lin, Z.W.[Zhi-Wei], Liu, Z.[Zhe], Xia, Z.Y.[Zhong-Yu], Wang, X.H.[Xin-Hao], Wang, Y.T.[Yong-Tao], Qi, S.X.[Sheng-Xiang], Dong, Y.[Yang], Dong, N.[Nan], Zhang, L.[Le], Zhu, C.[Ce],
RCBEVDet: Radar-Camera Fusion in Bird's Eye View for 3D Object Detection,
CVPR24(14928-14937)
IEEE DOI Code:
WWW Link. 2410
Radar cross-sections, Object detection, Radar, Detectors, Benchmark testing, Feature extraction, Radar-camera Fusion, Birds Eye View BibRef

Long, Y.F.[Yun-Fei], Morris, D.[Daniel], Liu, X.M.[Xiao-Ming], Castro, M.[Marcos], Chakravarty, P.[Punarjay], Narayanan, P.[Praveen],
Full-Velocity Radar Returns by Radar-Camera Fusion,
ICCV21(16178-16187)
IEEE DOI 2203
Laser radar, Closed-form solutions, Estimation, Radar, Radar imaging, Cameras, Doppler radar, 3D from multiview and other sensors BibRef

Pang, S.[Su], Morris, D.[Daniel], Radha, H.[Hayder],
Fast-CLOCs: Fast Camera-LiDAR Object Candidates Fusion for 3D Object Detection,
WACV22(3747-3756)
IEEE DOI 2202
Visualization, Memory management, Pipelines, Graphics processing units, Object detection, Detectors, Vision Systems and Applications BibRef

Stäcker, L.[Lukas], Heidenreich, P.[Philipp], Rambach, J.[Jason], Stricker, D.[Didier],
Fusion Point Pruning for Optimized 2D Object Detection with Radar-Camera Fusion,
WACV22(1275-1282)
IEEE DOI 2202
Uncertainty, Fuses, Radar detection, Radar, Object detection, Radar imaging, Vision for Robotics BibRef

Fadadu, S.[Sudeep], Pandey, S.[Shreyash], Hegde, D.[Darshan], Shi, Y.[Yi], Chou, F.C.[Fang-Chieh], Djuric, N.[Nemanja], Vallespi-Gonzalez, C.[Carlos],
Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving,
WACV22(3292-3300)
IEEE DOI 2202
Laser radar, Object detection, Predictive models, Feature extraction, Cameras, Prediction algorithms, Trajectory, Deep Learning BibRef

Petrushevsky, N., Manzoni, M., Guarnieri, A.M.,
High-resolution Urban Mapping By Fusion of SAR and Optical Data,
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Xu, H.R.[Hao-Ran], He, M.Y.[Ming-Yi], Rao, Z.B.[Zhi-Bo], Li, W.Y.[Wen-Yao],
Him-Net: A New Neural Network Approach for SAR and Optical Image Template Matching1,
ICIP21(3827-3831)
IEEE DOI 2201
Integrated optics, Optical losses, Heating systems, Image matching, Neural networks, Optical computing, Optical fiber networks, SAR BibRef

Han, C.L.[Chun-Lei], Lu, Y.[Yao], Yang, D.[Di], Wang, H.M.[Hong-Mei], Li, L.[Lin], Wang, X.Y.[Xiao-Yan],
Multi-source Collaborative Target Classification Based on ISAR and Infrared Image,
ICIVC21(149-153)
IEEE DOI 2112
Image recognition, Target recognition, Fuses, Neural networks, Collaboration, Feature extraction, Information technology, target recognition BibRef

Dong, X.[Xu], Zhuang, B.[Binnan], Mao, Y.X.[Yun-Xiang], Liu, L.C.[Lange-Chuan],
Radar Camera Fusion via Representation Learning in Autonomous Driving,
MULA21(1672-1681)
IEEE DOI 2109
Radar measurements, Radar detection, Cameras, Cognition, Sensor systems, Sensors, Pins BibRef

Nabati, R.[Ramin], Qi, H.R.[Hai-Rong],
CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection,
WACV21(1526-1535)
IEEE DOI 2106
Spaceborne radar, Radar detection, Object detection, Radar imaging, Sensor fusion, Cameras BibRef

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Radar + RGB Fusion For Robust Object Detection In Autonomous Vehicle,
ICIP20(1986-1990)
IEEE DOI 2011
Radar imaging, Feature extraction, Sensors, Object detection, Cameras, Radar detection, Object Detection, Radar Signals, Vision, Autonomous Vehicle BibRef

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Artificial neural networks, Computational modeling, Imaging, Iron, Minimization, Neurons, Radar imaging, Maximum Entropy, Multi-Sensor Imaging Radars, Neural Network, Remote Sensing, Sensor, Fusion BibRef

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An Automatic Optical and SAR Image Registration Method Using Iterative Multi-level And Refinement Model,
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On The Challenges In Stereogrammetric Fusion Of SAR and Optical Imagery For Urban Areas,
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Ai, C., Feng, T., Wang, J., Zhang, S.,
A Novel Image Registration Algorithm for SAR and Optical Images Based on Virtual Points,
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Cheng, C.Q., Zhang, J.X., Huang, G.M., Luo, C.F.,
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Shamsoddini, A.,
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Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., Ertl, M.,
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Bao, C., Huang, G., Yang, S.,
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Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Fusion, Aerial and Ground Images .