11.14.3.9.6 Inpainting, Interpolation Methods

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

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, Pattern recognition, 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 .