11.14.3.9.6 Inpainting, Interpolation Methods

Chapter Contents (Back)
Inpainting. Interpolation.
See also Outpainting, Extrapolation.

Ballester, C., Bertalmio, M., Caselles, V., Sapiro, G., Verdera, J.,
Filling-in by joint interpolation of vector fields and gray levels,
IP(10), No. 8, August 2001, pp. 1200-1211.
IEEE DOI 0108
BibRef
And: A1, A3, A5, A2, A4:
A Variational Model for Filling-in Gray Level and Color Images,
ICCV01(I: 10-16).
IEEE DOI 0106

See also Comprehensive Framework for Image Inpainting, A. BibRef

Arias, P.[Pablo], Facciolo, G.[Gabriele], Caselles, V.[Vicent], Sapiro, G.[Guillermo],
A Variational Framework for Exemplar-Based Image Inpainting,
IJCV(93), No. 3, July 2011, pp. 319-347.
WWW Link. 1104
BibRef
Earlier: A2, A1, A3, A4:
Exemplar-Based Interpolation of Sparsely Sampled Images,
EMMCVPR09(331-344).
Springer DOI 0908
BibRef
Earlier: A1, A3, A4, Only:
A Variational Framework for Non-local Image Inpainting,
EMMCVPR09(345-358).
Springer DOI 0908
Code:
See also Variational Framework for Non-Local Inpainting.
See also Variational Model for Gradient-Based Video Editing, A.
See also Combined First and Second Order Total Variation Inpainting using Split Bregman. BibRef

Fedorov, V.[Vadim], Facciolo, G.[Gabriele], Arias, P.[Pablo],
Variational Framework for Non-Local Inpainting,
IPOL(5), 2015, pp. 362-386.
DOI Link 1601
Code, Inpainting.
See also Variational Framework for Exemplar-Based Image Inpainting, A. BibRef

Masnou, S.,
Disocclusion: a variational approach using level lines,
IP(11), No. 2, February 2002, pp. 68-76.
IEEE DOI 0202
Recovery of occluded areas by interpolation. BibRef

Masnou, S., Morel, J.M.,
Level lines based disocclusion,
ICIP98(III: 259-263).
IEEE DOI 9810
BibRef

Fukushima, T.[Tsumoru], Onishi, H.[Hiroshi], Yamashita, H.[Haruo],
Method for interpolating missing pixels and an apparatus employing the method,
US_Patent5,570,436, Oct 29, 1996
WWW Link. BibRef 9610

Nemirovsky, S.[Shira], Porat, M.[Moshe],
On texture and image interpolation using Markov models,
SP:IC(24), No. 3, March 2009, pp. 139-157.
Elsevier DOI 0903
Markov models; Wide-sense Markov; Autocorrelation function; Sampling; High resolution; Low resolution; Texture interpolation; Fidelity criterion for texture reconstruction; Subjective forced-choice test BibRef

Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Missing Intensity Interpolation Using a Kernel PCA-Based POCS Algorithm and its Applications,
IP(19), No. 2, February 2011, pp. 417-432.
IEEE DOI 1102
BibRef
Earlier:
POCS-Based Iterative Reconstruction Algorithm of Missing Textures,
ICIP07(III: 101-104).
IEEE DOI 0709
BibRef

Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Missing Image Data Reconstruction Based on Adaptive Inverse Projection via Sparse Representation,
MultMed(13), No. 5, 2011, pp. 974-992.
IEEE DOI 1110
BibRef

Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Missing Texture Reconstruction Method Based on Error Reduction Algorithm Using Fourier Transform Magnitude Estimation Scheme,
IP(22), No. 3, March 2013, pp. 1252-1257.
IEEE DOI 1301
BibRef

Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Adaptive Subspace-Based Inverse Projections via Division Into Multiple Sub-Problems for Missing Image Data Restoration,
IP(25), No. 12, December 2016, pp. 5971-5986.
IEEE DOI 1612
image representation BibRef

Ogawa, T.[Takahiro], Haseyama, M.[Miki], Kitajima, H.,
Reconstruction Method of Missing Texture Using Error Reduction Algorithm,
ICIP05(II: 1026-1029).
IEEE DOI 0512
BibRef

Kumwilaisak, W.[Wuttipong], Kuo, C.C.J.[C.C. Jay],
Spatial error concealment with sequence-aligned texture modeling and adaptive directional recovery,
JVCIR(22), No. 2, February 2011, pp. 164-177.
Elsevier DOI 1102
Spatial error concealment; Global pixel alignment; Local pixel alignment; Correspondence association; Directional recovery; Geometric interpolation; Texture pattern mode; Peak-signal-to-noise ratio BibRef

Bhattacharjee, S., Mitra, P., Ghosh, S.K.,
Spatial Interpolation to Predict Missing Attributes in GIS Using Semantic Kriging,
GeoRS(52), No. 8, August 2014, pp. 4771-4780.
IEEE DOI 1403
Blend spatial feature analysis with Kriging for predicting missing data. Correlation BibRef

Chung, B.J.[Byung-Jin], Yim, C.H.[Chang-Hoon],
Hybrid error concealment method combining exemplar-based image inpainting and spatial interpolation,
SP:IC(29), No. 10, 2014, pp. 1121-1137.
Elsevier DOI 1411
Image reconstruction BibRef

Deng, M.[Min], Fan, Z.[Zide], Liu, Q.L.[Qi-Liang], Gong, J.Y.[Jian-Ya],
A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets,
IJGI(5), No. 2, 2016, pp. 13.
DOI Link 1603
BibRef

Ceko, M.[Matthew], Guinard, A.[Arnaud], Svalbe, I.[Imants],
Symmetric Masks for In-fill Pixel Interpolation on Discrete p:q Lattices,
JMIV(60), No. 3, March 2018, pp. 304-312.
Springer DOI 1804
BibRef
Earlier: A3, A2, Only: DGCI16(233-243).
WWW Link. 1606
BibRef

Liu, Q.G.[Qie-Gen], Li, S.Q.[San-Qian], Xiao, J.[Jing], Zhang, M.H.[Ming-Hui],
Multi-filters guided low-rank tensor coding for image inpainting,
SP:IC(73), 2019, pp. 70-83.
Elsevier DOI 1904
BibRef
Earlier: A2, A1, Only: ICIVC17(418-422)
IEEE DOI 1708
Image inpainting, Multi-filters, Low-rank, Tensor coding, Higher-order singular value decomposition, Gradient descent, Weighted aggregation. Boats, Hair, Image edge detection, Interpolation, Tensile stress, HOSVD decomposition, gradient descent procedure, image inpainting, low-rank, multi-filters, tensor, coding BibRef

Lu, H.Y.[Hong-Yang], Li, S.Q.[San-Qian], Liu, Q.G.[Qie-Gen], Wang, Y.H.[Yu-Hao],
MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration,
ICIP17(2104-2108)
IEEE DOI 1803
Indexes, HOSVD decomposition, Image restoration, Low-rank tensor coding, Multi-filters BibRef

Huang, J., Dragotti, P.L.[Pier Luigi],
Photo Realistic Image Completion via Dense Correspondence,
IP(27), No. 11, November 2018, pp. 5234-5247.
IEEE DOI 1809
image colour analysis, image matching, image retrieval, interpolation, realistic images, input image, exemplar image, EM algorithm BibRef

Zhang, K., Crooks, E., Orlando, A.,
Compensated Convexity Methods for Approximations and Interpolations of Sampled Functions in Euclidean Spaces: Applications to Contour Lines, Sparse Data, and Inpainting,
SIIMS(11), No. 4, 2018, pp. 2368-2428.
DOI Link 1901
BibRef

Holloway, J.[Jacinta], Helmstedt, K.J.[Kate J.], Mengersen, K.[Kerrie], Schmidt, M.[Michael],
A Decision Tree Approach for Spatially Interpolating Missing Land Cover Data and Classifying Satellite Images,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
BibRef


Liu, H.P.[Hai-Peng], Wang, Y.[Yang], Qian, B.[Biao], Wang, M.[Meng], Rui, Y.[Yong],
Structure Matters: Tackling the Semantic Discrepancy in Diffusion Models for Image Inpainting,
CVPR24(8038-8047)
IEEE DOI Code:
WWW Link. 2410
Codes, Art, Semantics, Noise reduction, Noise, Neural networks, Diffusion Models, Image Inpainting BibRef

Peter, P.,
Fast Inpainting-Based Compression: Combining Shepard Interpolation with Joint Inpainting and Prediction,
ICIP19(3557-3561)
IEEE DOI 1910
Image compression, inpainting, prediction BibRef

Augustin, M.[Matthias], Weickert, J.[Joachim], Andris, S.[Sarah],
Pseudodifferential Inpainting: The Missing Link Between PDE- and RBF-Based Interpolation,
SSVM19(67-78).
Springer DOI 1909
BibRef

Ren, Y., Yu, X., Zhang, R., Li, T.H., Liu, S., Li, G.,
StructureFlow: Image Inpainting via Structure-Aware Appearance Flow,
ICCV19(181-190)
IEEE DOI 2004
image denoising, image reconstruction, image restoration, image segmentation, image texture, neural nets, smoothing methods, Visualization BibRef

Allain, P.[Pierre], Guillo, L.[Laurent], Guillemot, C.[Christine],
Fast Light Field Inpainting Propagation Using Angular Warping and Color-Guided Disparity Interpolation,
ACIVS18(559-570).
Springer DOI 1810
BibRef

Chen, R., Jia, H., Xie, X., Gao, W.,
Correlation preserving on graphs for image denoising,
ICIP17(1876-1880)
IEEE DOI 1803
BibRef
Earlier:
A structure-preserving image restoration method with high-level ensemble constraints,
VCIP16(1-4)
IEEE DOI 1701
BibRef
Earlier:
A HVS-guided approach for real-time image interpolation,
VCIP15(1-4)
IEEE DOI 1605
Europe, IEEE Multimedia, Indexes, Multimedia communication, TV, low-rank. Contracts BibRef

Guo, K.[Kai], Yang, X.K.[Xiao-Kang], Zhang, R.[Rui], Yu, S.Y.[Song-Yu], Zha, H.Y.[Hong-Yuan],
Interpolating fine textures with fields of experts prior,
ICIP09(353-356).
IEEE DOI 0911
BibRef

Kim, J.H.[Ji Hoon], Lee, S.H.[Sang Hwa], Cho, N.I.[Nam Ik],
Bayesian Image Interpolation Based on the Learning and Estimation of Higher Bandwavelet Coefficients,
ICIP06(685-688).
IEEE DOI 0610
BibRef

Saito, T., Ishii, Y., Nakagawa, Y., Komatsu, T.,
Adaptable Image Interpolation with Skeleton-Texture Separation,
ICIP06(681-684).
IEEE DOI 0610
BibRef

Chessel, A., Fablet, R., Cao, F., Kervrann, C.,
Orientation Interpolation and Applications,
ICIP06(1561-1564).
IEEE DOI 0610
BibRef

Chessel, A.[Anatole], Cao, F.[Frederic], Fablet, R.[Ronan],
Interpolating Orientation Fields: An Axiomatic Approach,
ECCV06(IV: 241-254).
Springer DOI 0608
BibRef

Chandra, S.I.[Sun-Il], Petrou, M.[Maria], Piroddi, R.[Roberta],
Texture Interpolation Using Ordinary Kriging,
IbPRIA05(II:183).
Springer DOI 0509
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Inpainting, Patch Based Methods, Region Methods .


Last update:Apr 23, 2025 at 18:43:10