11.14.3.9.2 Missing Data, Fixing Problems

Chapter Contents (Back)
Inpainting. Missing Data. A somewhat arbitrary subset of Inpainting, but more large chunks.
See also Inpainting, Filling Holes, Fixing Problems.

Rane, S.D., Sapiro, G., Bertalmio, M.,
Structure and texture filling-in of missing image blocks in wireless transmission and compression applications,
IP(12), No. 3, March 2003, pp. 296-303.
IEEE DOI 0301
BibRef
Earlier: ICIP02(I: 317-320).
IEEE DOI 0210
BibRef

Bertalmio, M., Vese, L.A., Sapiro, G., Osher, S.J.,
Simultaneous structure and texture image inpainting,
IP(12), No. 8, August 2003, pp. 882-889.
IEEE DOI 0308
BibRef
Earlier: CVPR03(II: 707-712).
IEEE DOI 0307
BibRef
And:
Image filling-in in a decomposition space,
ICIP03(I: 853-856).
IEEE DOI 0312

See also Video Inpainting Under Constrained Camera Motion. BibRef

Bertalmio, M., Sapiro, G., Caselles, V., and Ballester, C.,
Image inpainting,
SIGGraph-2000(417-424). BibRef 0001

Yatziv, L., Sapiro, G., Levoy, M.,
Lightfield completion,
ICIP04(III: 1787-1790).
IEEE DOI 0505
Fill in gaps due to occlusions. BibRef

Bertalmio, M.,
Strong-Continuation, Contrast-Invariant Inpainting With a Third-Order Optimal PDE,
IP(15), No. 7, July 2006, pp. 1934-1938.
IEEE DOI 0606
BibRef

Ballester, C., Caselles, V., Verdera, J.,
A variational model for disocclusion,
ICIP03(III: 677-680).
IEEE DOI 0312
BibRef

Lin, H.J.[Hwei-Jen], Wang, C.W.[Chun-Wei], Hsieh, Y.C.[Yuan-Chun], Kao, Y.T.[Yang-Ta],
Image restoration with broken curve prediction,
IJCVR(1), No. 1, 2009, pp. 110-120.
DOI Link 0911
Detect missing edges for inpainting. BibRef

Yang, S.B.[Shiueng-Bien], Liang, T.W.[Ting-Wen],
Image Restoration Based on Smooth Gray-level Detection and Line Prediction Method for Large Missing Regions,
IJIG(12), No. 2, April 2012, pp. 1250013.
DOI Link 1205
BibRef

Lobato, F.[Fabio], Sales, C.[Claudomiro], Araujo, I.[Igor], Tadaiesky, V.[Vincent], Dias, L.[Lilian], Ramos, L.[Leonardo], Santana, A.[Adamo],
Multi-objective genetic algorithm for missing data imputation,
PRL(68, Part 1), No. 1, 2015, pp. 126-131.
Elsevier DOI 1512
Missing data BibRef

Madathil, B.[Baburaj], George, S.N.[Sudhish N.],
A novel dictionary-based approach for missing sample recovery of signals in manifold,
SIViP(11), No. 2, February 2017, pp. 283-290.
Springer DOI 1702
BibRef

Fortunati, S.[Stefano], Gini, F.[Fulvio], Greco, M.S.[Maria S.], Richmond, C.D.[Christ D.],
Performance Bounds for Parameter Estimation under Misspecified Models: Fundamental Findings and Applications,
SPMag(34), No. 6, November 2017, pp. 142-157.
IEEE DOI 1712
Bayes methods, Biological system modeling, Data models, Estimation theory, Maximum likelihood estimation, Signal processing algorithms. Missing data. BibRef

Gerber, F., de Jong, R., Schaepman, M.E., Schaepman-Strub, G., Furrer, R.,
Predicting Missing Values in Spatio-Temporal Remote Sensing Data,
GeoRS(56), No. 5, May 2018, pp. 2841-2853.
IEEE DOI 1805
Indexes, MODIS, Open source software, Prediction methods, Remote sensing, Uncertainty, Alaska, uncertainty BibRef

Dai, J., Hu, H., Hu, Q., Huang, W., Zheng, N., Liu, L.,
Locally Linear Approximation Approach for Incomplete Data,
Cyber(48), No. 6, June 2018, pp. 1720-1732.
IEEE DOI 1805
Approximation algorithms, Computer science, Correlation, Image reconstruction, Linear approximation, matrix completion BibRef

Zhang, Q., Yuan, Q., Zeng, C., Li, X., Wei, Y.,
Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network,
GeoRS(56), No. 8, August 2018, pp. 4274-4288.
IEEE DOI 1808
image reconstruction, neural nets, remote sensing, unified spatial-temporal-spectral framework, unified deep CNN, spatial-temporal-spectral BibRef

Liu, X.M.[Xiao-Ming], Wang, M.[Menghua],
Gap Filling of Missing Data for VIIRS Global Ocean Color Products Using the DINEOF Method,
GeoRS(56), No. 8, August 2018, pp. 4464-4476.
IEEE DOI 1808
atmospheric techniques, infrared imaging, interpolation, oceanographic regions, oceanographic techniques, radiometers, Visible Infrared Imaging Radiometer Suite (VIIRS) BibRef

Liu, X.M.[Xiao-Ming], Wang, M.[Menghua],
Filling the Gaps of Missing Data in the Merged VIIRS SNPP/NOAA-20 Ocean Color Product Using the DINEOF Method,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
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, Y., Long, Z., Huang, H., Zhu, C.,
Low CP Rank and Tucker Rank Tensor Completion for Estimating Missing Components in Image Data,
CirSysVideo(30), No. 4, April 2020, pp. 944-954.
IEEE DOI 2004
Optimization, Matrix decomposition, Data structures, Convex functions, Numerical models, Minimization methods, Tucker decomposition BibRef

Chai, X., Tang, G., Wang, S., Peng, R., Chen, W., Li, J.,
Deep Learning for Regularly Missing Data Reconstruction,
GeoRS(58), No. 6, June 2020, pp. 4406-4423.
IEEE DOI 2005
Convolutional neural networks (CNNs), deep learning (DL), missing data reconstruction BibRef

Chi, Y.F.[Yu-Feng], Wu, Z.F.[Zhi-Feng], Liao, K.[Kuo], Ren, Y.[Yin],
Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Dong, B.[Bin], Ju, H.C.[Hao-Cheng], Lu, Y.P.[Yi-Ping], Shi, Z.Q.[Zuo-Qiang],
CURE: Curvature Regularization for Missing Data Recovery,
SIIMS(13), No. 4, 2020, pp. 2169-2188.
DOI Link 2012
BibRef

Xu, H.[Hanwen], Tang, X.[Xinming], Ai, B.[Bo], Gao, X.M.[Xiao-Ming], Yang, F.[Fanlin], Wen, Z.[Zhen],
Missing data reconstruction in VHR images based on progressive structure prediction and texture generation,
PandRS(171), 2021, pp. 266-277.
Elsevier DOI 2012
Missing data reconstruction, VHR images, Progressive structure prediction, Texture generation, Deep learning BibRef

Case, N.[Nicola], Vitti, A.[Alfonso],
Reconstruction of Multi-Temporal Satellite Imagery by Coupling Variational Segmentation and Radiometric Analysis,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
Correcting for missing data from sensors. BibRef

Teodoro, A.M., Bioucas-Dias, J.M., Figueiredo, M.A.T.,
Block-Gaussian-Mixture Priors for Hyperspectral Denoising and Inpainting,
GeoRS(59), No. 3, March 2021, pp. 2478-2486.
IEEE DOI 2103
Noise reduction, Noise measurement, Gaussian mixture model, Feature extraction, Data mining, Transforms, image denoising BibRef

Zdunek, R.[Rafal], Sadowski, T.[Tomasz],
Image completion with approximate convex hull tensor decomposition,
SP:IC(95), 2021, pp. 116276.
Elsevier DOI 2106
Image completion, Convex-hull algorithm, Near-separable tensor decompositions, Non-negative tensor factorization BibRef

Barmherzig, D.A.[David A.], Barnett, A.H.[Alex H.], Epstein, C.L.[Charles L.], Greengard, L.F.[Leslie F.], Magland, J.F.[Jeremy F.], Rachh, M.[Manas],
Recovering Missing Data in Coherent Diffraction Imaging,
SIIMS(14), No. 2, 2021, pp. 620-644.
DOI Link 2107
BibRef

Xie, M.H.[Ming-Hong], Wang, J.X.[Jia-Xin], Zhang, Y.[Yafei],
A unified framework for damaged image fusion and completion based on low-rank and sparse decomposition,
SP:IC(98), 2021, pp. 116400.
Elsevier DOI 2109
Image fusion, Image completion, Image decomposition, Low-rank and sparse representation, Dictionary learning BibRef


Yoon, S., Sull, S.,
GAMIN: Generative Adversarial Multiple Imputation Network for Highly Missing Data,
CVPR20(8453-8461)
IEEE DOI 2008
Generators, Generative adversarial networks, Stochastic processes, Measurement, Unsupervised learning, Prediction methods BibRef

Lee, D.W.[Dong-Wook], Kim, J.[Junyoung], Moon, W.J.[Won-Jin], Ye, J.C.[Jong Chul],
CollaGAN: Collaborative GAN for Missing Image Data Imputation,
CVPR19(2482-2491).
IEEE DOI 2002
BibRef

Chen, X.,
An Improved Self-Representation Approach for Missing Value Imputation,
ICPR18(1450-1455)
IEEE DOI 1812
Roads, Sensors, Optimization, Estimation, Data analysis, Matrix decomposition, Indexes, graph regularization, missing values BibRef

Yokota, T.[Tatsuya], Erem, B.[Burak], Guler, S.[Seyhmus], Warfield, S.K.[Simon K.], Hontani, H.[Hidekata],
Missing Slice Recovery for Tensors Using a Low-Rank Model in Embedded Space,
CVPR18(8251-8259)
IEEE DOI 1812
Delays, Transforms, Minimization, Standards, Optimization, Matrix decomposition BibRef

Tran, L.[Luan], Liu, X.M.[Xiao-Ming], Zhou, J.Y.[Jia-Yu], Jin, R.[Rong],
Missing Modalities Imputation via Cascaded Residual Autoencoder,
CVPR17(4971-4980)
IEEE DOI 1711
Some of the multi-modal data is missing. Data models, Genetic algorithms, Matrix decomposition, Object recognition, Sensors, Training BibRef

Xu, Z., Li, Y., Huang, J.,
Accelerated sparse optimization for missing data completion,
ICPR16(1267-1272)
IEEE DOI 1705
Closed-form solutions, Convergence, Matrix decomposition, Minimization, TV, Visualization BibRef

Campos, S.[Sergio], Pizarro, L.[Luis], Valle, C.[Carlos], Gray, K.R.[Katherine R.], Rueckert, D.[Daniel], Allende, H.[Héctor],
Evaluating Imputation Techniques for Missing Data in ADNI: A Patient Classification Study,
CIARP15(3-10).
Springer DOI 1511
BibRef

Ryazanov, V.[Vladimir],
Some Imputation Algorithms for Restoration of Missing Data,
CIARP11(372-379).
Springer DOI 1111
BibRef

Herlin, I.[Isabelle], Béréziat, D.[Dominique], Mercier, N.[Nicolas],
Recovering Missing Data on Satellite Images,
SCIA11(697-707).
Springer DOI 1105
BibRef

Corrigan, D., Harte, N., Kokaram, A.,
Pathological Motion Detection for Robust Missing Data Treatment in Degraded Archived Media,
ICIP06(621-624).
IEEE DOI 0610
BibRef

Gan, X.C.[Xiang-Chao], Liew, A.W.C.[Alan Wee-Chung], Yan, H.[Hong],
Microarray Missing Data Imputation based on a Set Theoretic Framework and Biological Constraints,
ICPR06(III: 842-845).
IEEE DOI 0609
BibRef

Han, F.[Feng], Zhu, S.C.[Song-Chun],
Bayesian reconstruction of 3D shapes and scenes from a single image,
HLK03(12-20).
IEEE Abstract. 0402
Fill in missing parts of image from model. BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Inpainting Face Images, Facial Images .


Last update:Nov 1, 2021 at 09:26:50