Clausen, C.[Clifford],
Wechsler, H.[Harry],
Color image compression using PCA and backpropagation learning,
PR(33), No. 9, September 2000, pp. 1555-1560.
WWW Link.
0005
BibRef
Zheng, M.,
Bu, J.,
Chen, C.A.,
Wang, C.,
Zhang, L.,
Qiu, G.,
Cai, D.,
Graph Regularized Sparse Coding for Image Representation,
IP(20), No. 5, May 2011, pp. 1327-1336.
IEEE DOI
1104
Find a basis set capturing high-level semantics in the data and learn
sparse coordinates in terms of the basis set.
BibRef
Zhang, C.,
He, X.,
Image Compression by Learning to Minimize the Total Error,
CirSysVideo(23), No. 4, April 2013, pp. 565-576.
IEEE DOI
1304
BibRef
Li, Y.[Yang],
Tao, X.M.[Xiao-Ming],
Lu, J.H.[Jian-Hua],
Hybrid model-and-object-based real-time conversational video coding,
SP:IC(35), No. 1, 2015, pp. 9-19.
Elsevier DOI
1506
Model-based video coding
BibRef
Xu, M.[Mai],
Li, S.X.[Sheng-Xi],
Lu, J.H.[Jian-Hua],
Zhu, W.[Wenwu],
Compressibility Constrained Sparse Representation With Learnt
Dictionary for Low Bit-Rate Image Compression,
CirSysVideo(24), No. 10, October 2014, pp. 1743-1757.
IEEE DOI
1411
BibRef
Earlier: A1, A3, A4, Only:
Sparse representation of texture patches for low bit-rate image
compression,
VCIP12(1-6).
IEEE DOI
1302
BibRef
Damerchilu, B.[Bahman],
Norouzzadeh, M.S.[Mohammad Sadegh],
Meybodi, M.R.[Mohammad Reza],
Motion estimation using learning automata,
MVA(27), No. 7, October 2016, pp. 1047-1061.
Springer DOI
1610
BibRef
Xu, M.[Mai],
Jiang, L.[Lai],
Ye, Z.T.[Zhao-Ting],
Wang, Z.[Zulin],
Bottom-up saliency detection with sparse representation of learnt
texture atoms,
PR(60), No. 1, 2016, pp. 348-360.
Elsevier DOI
1609
BibRef
Earlier: A2, A1, A3, A4:
Image Saliency Detection with Sparse Representation of Learnt Texture
Atoms,
RSL-CV15(894-902)
IEEE DOI
1602
Visual attention
Databases
BibRef
Xu, M.[Mai],
Jiang, L.[Lai],
Sun, X.,
Ye, Z.T.[Zhao-Ting],
Wang, Z.[Zulin],
Learning to Detect Video Saliency With HEVC Features,
IP(26), No. 1, January 2017, pp. 369-385.
IEEE DOI
1612
computer vision
BibRef
Sun, Y.P.[Yi-Peng],
Tao, X.M.[Xiao-Ming],
Li, Y.[Yang],
Lu, J.H.[Jian-Hua],
Dictionary Learning for Image Coding Based on Multisample Sparse
Representation,
CirSysVideo(24), No. 11, November 2014, pp. 2004-2010.
IEEE DOI
1411
compressed sensing
BibRef
Chen, Z.,
He, T.,
Jin, X.,
Wu, F.,
Learning for Video Compression,
CirSysVideo(30), No. 2, February 2020, pp. 566-576.
IEEE DOI
2002
Image coding, Video compression, Spatiotemporal phenomena,
Image reconstruction, Transform coding, Codecs, Video coding,
PixelMotionCNN
BibRef
Ma, L.[Lin],
Zhao, D.B.[De-Bin],
Gao, W.[Wen],
Learning-based image restoration for compressed images,
SP:IC(27), No. 1, January 2012, pp. 54-65.
Elsevier DOI
1201
Image restoration; Compression artifacts; Primitive
BibRef
Liu, X.M.[Xian-Ming],
Cheung, G.[Gene],
Wu, X.L.[Xiao-Lin],
Zhao, D.B.[De-Bin],
Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding
of JPEG Images,
IP(26), No. 2, February 2017, pp. 509-524.
IEEE DOI
1702
BibRef
Earlier:
Inter-block consistent soft decoding of JPEG images with sparsity and
graph-signal smoothness priors,
ICIP15(1628-1632)
IEEE DOI
1512
Laplace equations.
graph signal processing; image decoding; sparse signal representation
BibRef
Liu, X.M.[Xian-Ming],
Wu, X.L.[Xiao-Lin],
Zhou, J.T.[Jian-Tao],
Zhao, D.B.[De-Bin],
Data-driven sparsity-based restoration of JPEG-compressed images in
dual transform-pixel domain,
CVPR15(5171-5178)
IEEE DOI
1510
BibRef
Liu, X.M.[Xian-Ming],
Wu, X.L.[Xiao-Lin],
Zhao, D.B.[De-Bin],
Sparsity-based soft decoding of compressed images in transform domain,
ICIP13(563-566)
IEEE DOI
1402
Decoding. Restore compressed images not decoded images.
BibRef
Yeh, C.H.[Chia-Hung],
Kang, L.W.[Li-Wei],
Chiou, Y.W.[Yi-Wen],
Lin, C.W.[Chia-Wen],
Jiang, S.J.F.[Shu-Jhen Fan],
Self-learning-based post-processing for image/video deblocking via
sparse representation,
JVCIR(25), No. 5, 2014, pp. 891-903.
Elsevier DOI
1406
BibRef
Earlier: A3, A1, A2, A4, A5:
Efficient image/video deblocking via sparse representation,
VCIP12(1-6).
IEEE DOI
1302
Blocking artifact
BibRef
Kang, L.W.,
Hsu, C.C.,
Zhuang, B.,
Lin, C.W.,
Yeh, C.H.,
Learning-Based Joint Super-Resolution and Deblocking for a Highly
Compressed Image,
MultMed(17), No. 7, July 2015, pp. 921-934.
IEEE DOI
1506
Dictionaries
BibRef
Zhang, B.C.[Bao-Chang],
Gu, J.X.[Jia-Xin],
Chen, C.[Chen],
Han, J.G.[Jun-Gong],
Su, X.B.[Xiang-Bo],
Cao, X.B.[Xian-Bin],
Liu, J.Z.[Jian-Zhuang],
One-two-one networks for compression artifacts reduction in remote
sensing,
PandRS(145), 2018, pp. 184-196.
Elsevier DOI
1810
Compression artifacts reduction, Remote sensing, Deep learning,
One-two-one network
BibRef
Gan, Z.L.[Zong-Liang],
Low Bit-Rate Compression Image Restoration through Subspace Joint
Regression Learning,
IEICE(E101-D), No. 10, October 2018, pp. 2539-2542.
WWW Link.
1810
BibRef
Wang, M.,
Xie, W.,
Meng, X.,
Zeng, H.,
Ngan, K.N.,
UHD Video Coding: A Light-Weight Learning-Based Fast Super-Block
Approach,
CirSysVideo(29), No. 10, October 2019, pp. 3083-3094.
IEEE DOI
1910
data compression, high definition video, image colour analysis,
image resolution, image texture, video coding, medium coding unit, HEVC
BibRef
Zhao, L.J.[Li-Jun],
Bai, H.H.[Hui-Hui],
Wang, A.[Anhong],
Zhao, Y.[Yao],
Learning a virtual codec based on deep convolutional neural network
to compress image,
JVCIR(63), 2019, pp. 102589.
Elsevier DOI
1909
Image representation, Image compression, Soft-projection,
Virtual codec, Post-processing
BibRef
Yu, L.W.[Liang-Wei],
Shen, L.Q.[Li-Quan],
Yang, H.[Hao],
Wang, L.[Lu],
An, P.[Ping],
Quality Enhancement Network via Multi-Reconstruction Recursive
Residual Learning for Video Coding,
SPLetters(26), No. 4, April 2019, pp. 557-561.
IEEE DOI
1903
Image reconstruction, Feature extraction, Training, Image coding,
Encoding, Periodic structures, Compression algorithms,
quality enhancement
BibRef
Liu, Y.[Ying],
Tountas, K.[Konstantinos],
Pados, D.A.[Dimitris A.],
Batalama, S.N.[Stella N.],
Medley, M.J.[Michael J.],
L1-Subspace Tracking for Streaming Data,
PR(97), 2020, pp. 106992.
Elsevier DOI
1910
Dimensionality reduction, Eigenvector decomposition,
Internet-of-Things, -norm, Outliers, Subspace learning
BibRef
Fu, H.S.[Hai-Sheng],
Liang, F.[Feng],
Lei, B.[Bo],
Bian, N.[Nai],
Zhang, Q.[Qian],
Akbari, M.[Mohammad],
Liang, J.[Jie],
Tu, C.J.[Cheng-Jie],
Improved hybrid layered image compression using deep learning and
traditional codecs,
SP:IC(82), 2020, pp. 115774.
Elsevier DOI
2001
Deep learning-based image coding, Layered image coding,
Residual coding, Convolutional neural network, Autoencoder
BibRef
Song, Q.,
Xiong, R.,
Fan, X.,
Liu, D.,
Wu, F.,
Huang, T.,
Gao, W.,
Compressed Image Restoration via Artifacts-Free PCA Basis Learning
and Adaptive Sparse Modeling,
IP(29), 2020, pp. 7399-7413.
IEEE DOI
2007
Compressed image restoration, sparse modeling,
paired PCA learning, adaptive distribution modeling
BibRef
Liu, J.,
Liu, D.,
Yang, W.,
Xia, S.,
Zhang, X.,
Dai, Y.,
A Comprehensive Benchmark for Single Image Compression Artifact
Reduction,
IP(29), 2020, pp. 7845-7860.
IEEE DOI
2007
Compression artifacts removal, benchmark, side information,
loop filter, deep learning
BibRef
Cheng, Z.,
Sun, H.,
Takeuchi, M.,
Katto, J.,
Energy Compaction-Based Image Compression Using Convolutional
AutoEncoder,
MultMed(22), No. 4, April 2020, pp. 860-873.
IEEE DOI
2004
Image compression, convolutional autoencoder,
optimum bit allocation, energy compaction
BibRef
Yeo, Y.,
Shin, Y.,
Sagong, M.,
Kim, S.,
Ko, S.,
Simple Yet Effective Way for Improving the Performance of Lossy Image
Compression,
SPLetters(27), 2020, pp. 530-534.
IEEE DOI
2005
Convolutional neural network, deep learning, image compression
BibRef
Cai, J.,
Cao, Z.,
Zhang, L.,
Learning a Single Tucker Decomposition Network for Lossy Image
Compression With Multiple Bits-per-Pixel Rates,
IP(29), 2020, pp. 3612-3625.
IEEE DOI
2002
Lossy image compression, convolutional neural networks, tucker decomposition
BibRef
Schiopu, I.,
Munteanu, A.,
Deep-Learning-Based Lossless Image Coding,
CirSysVideo(30), No. 7, July 2020, pp. 1829-1842.
IEEE DOI
2007
Image coding, Cameras, Context modeling, Tools, Codecs,
Prediction methods, Standards, Machine learning, image coding, context modeling
BibRef
Liao, L.[Liang],
Xiao, J.[Jing],
Li, Y.T.[Ya-Ting],
Wang, M.[Mi],
Hu, R.M.[Rui-Min],
Learned Representation of Satellite Image Series for Data Compression,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
Long term background redundancy.
BibRef
Klopp, J.P.[Jan P.],
Chen, L.G.[Liang-Gee],
Chien, S.Y.[Shao-Yi],
Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video
Coding,
IP(29), 2020, pp. 6372-6385.
IEEE DOI
2006
Image coding, Redundancy, Decoding, Neural networks,
Complexity theory, Video codecs, Noise reduction, Video coding,
machine learning
BibRef
Paul, S.,
Norkin, A.,
Bovik, A.C.,
Speeding Up VP9 Intra Encoder With Hierarchical Deep Learning-Based
Partition Prediction,
IP(29), 2020, pp. 8134-8148.
IEEE DOI
2008
Machine learning, Image coding, Databases, Encoding, Video coding,
Task analysis, Video codecs, VP9, video encoding, block partitioning,
machine learning
BibRef
Sun, H.,
Liu, C.,
Katto, J.,
Fan, Y.,
An Image Compression Framework with Learning-based Filter,
CLIC20(602-606)
IEEE DOI
2008
Image color analysis, Principal component analysis, Image coding,
Image reconstruction, Distortion, Correlation, Covariance matrices
BibRef
Tao, H.,
Qian, J.,
Yu, L.,
Wang, H.,
Zhang, W.,
Li, Z.,
Wang, N.,
Zeng, X.,
Post-Processing Network Based on Dense Inception Attention for Video
Compression,
CLIC20(547-551)
IEEE DOI
2008
Encoding, Video compression, Video coding, Image coding,
Feature extraction, Kernel, Standards
BibRef
Feng, R.,
Wu, Y.,
Guo, Z.,
Zhang, Z.,
Chen, Z.,
Learned Video Compression with Feature-level Residuals,
CLIC20(529-532)
IEEE DOI
2008
Image coding, Training, Optical imaging, Adaptive optics,
Motion compensation, Optical distortion, Decoding
BibRef
Akutsu, H.,
Suzuki, A.,
Zhong, Z.,
Aizawa, K.,
Ultra Low Bitrate Learned Image Compression by Selective Detail
Decoding,
CLIC20(524-528)
IEEE DOI
2008
Decoding, Image coding, Entropy, Training, Bit rate,
Random access memory, Indexes
BibRef
He, G.,
Wu, C.,
Li, L.,
Zhou, J.,
Wang, X.,
Zheng, Y.,
Yu, B.,
Xie, W.,
A Video Compression Framework Using an Overfitted Restoration Neural
Network,
CLIC20(593-597)
IEEE DOI
2008
Video compression, Image restoration, Neural networks, Training,
Decoding, Computer vision, Pattern recognition
BibRef
Zou, N.,
Zhang, H.,
Cricri, F.,
Tavakoli, H.R.,
Lainema, J.,
Aksu, E.,
Hannuksela, M.,
Rahtu, E.,
End-to-End Learning for Video Frame Compression with Self-Attention,
CLIC20(580-584)
IEEE DOI
2008
Decoding, Neural networks, Tensile stress, Context modeling,
Image coding, Adaptation models, Probability distribution
BibRef
Lin, C.,
Yao, J.,
Chen, F.,
Wang, L.,
A Spatial RNN Codec for End-to-End Image Compression,
CVPR20(13266-13274)
IEEE DOI
2008
Image coding, Quantization (signal), Standards, Entropy,
Computational modeling, Redundancy, Transforms
BibRef
Chin, T.,
Ding, R.,
Zhang, C.,
Marculescu, D.,
Towards Efficient Model Compression via Learned Global Ranking,
CVPR20(1515-1525)
IEEE DOI
2008
Complexity theory, Computer architecture, Art, Drones,
Autonomous robots, Computational modeling
BibRef
Quach, M.,
Valenzise, G.,
Dufaux, F.,
Learning Convolutional Transforms for Lossy Point Cloud Geometry
Compression,
ICIP19(4320-4324)
IEEE DOI
1910
point cloud geometry compression, convolutional neural network,
rate-distortion optimization
BibRef
Mentzer, F.[Fabian],
Agustsson, E.[Eirikur],
Tschannen, M.[Michael],
Timofte, R.[Radu],
Van Gool, L.J.[Luc J.],
Practical Full Resolution Learned Lossless Image Compression,
CVPR19(10621-10630).
IEEE DOI
2002
BibRef
Yang, J.,
Yang, C.,
Ma, Y.,
Liu, S.,
Wang, R.,
Learned Low Bit-rate Image Compression with Adversarial Mechanism,
CLIC20(575-579)
IEEE DOI
2008
Image coding, Image reconstruction, Decoding, Training, Entropy,
Estimation, Distortion
BibRef
Huang, C.C.[Ching-Chun],
Nguyen, T.P.[Thanh-Phat],
Lai, C.T.[Chen-Tung],
Multi-Channel Multi-Loss Deep Learning Based Compression Model of
Color Images,
ICIP19(4524-4528)
IEEE DOI
1910
CNN, Deep image compression, Color shift reduction
BibRef
Lin, J.,
Liu, D.,
Li, H.,
Wu, F.,
M-LVC: Multiple Frames Prediction for Learned Video Compression,
CVPR20(3543-3551)
IEEE DOI
2008
Video compression, Image coding, Motion compensation, Entropy,
Encoding, Motion estimation, Transforms
BibRef
Yang, R.,
Mentzer, F.,
Van Gool, L.J.,
Timofte, R.,
Learning for Video Compression With Hierarchical Quality and
Recurrent Enhancement,
CVPR20(6627-6636)
IEEE DOI
2008
Image coding, Video compression, Decoding, Bidirectional control,
Streaming media, Rate-distortion, Correlation
BibRef
Mentzer, F.,
Van Gool, L.J.,
Tschannen, M.,
Learning Better Lossless Compression Using Lossy Compression,
CVPR20(6637-6646)
IEEE DOI
2008
Image coding, Image reconstruction, Probabilistic logic,
Entropy coding, Bit rate, Decoding, Transform coding
BibRef
Cheng, Z.X.[Zheng-Xue],
Sun, H.M.[He-Ming],
Takeuchi, M.[Masaru],
Katto, J.[Jiro],
Learned Image Compression With Discretized Gaussian Mixture
Likelihoods and Attention Modules,
CVPR20(7936-7945)
IEEE DOI
2008
BibRef
And: A1, A2, A4, Only:
Low Bitrate Image Compression with Discretized Gaussian Mixture
Likelihoods,
CLIC20(543-546)
IEEE DOI
2008
Image coding, Entropy, Standards, Visualization,
Training, Redundancy, Transform coding.
Convolution, Training, Decoding,
Pattern recognition, Bit rate
BibRef
Djelouah, A.,
Campos, J.,
Schaub-Meyer, S.,
Schroers, C.,
Neural Inter-Frame Compression for Video Coding,
ICCV19(6420-6428)
IEEE DOI
2004
data compression, decoding, image sequences, interpolation,
learning (artificial intelligence), motion compensation, Distortion
BibRef
Lucas, A.,
Lopez-Tapia, S.,
Molina, R.,
Katsaggelos, A.K.,
Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep
Learning for Inverse Imaging Problems,
ICIP19(3591-3595)
IEEE DOI
1910
Deep Neural Networks, Image and Video Processing, Inversion,
Fine-tuning, Artifacts, Data Consistency
BibRef
Rippel, O.,
Nair, S.,
Lew, C.,
Branson, S.,
Anderson, A.,
Bourdev, L.,
Learned Video Compression,
ICCV19(3453-3462)
IEEE DOI
2004
data compression, image sequences,
learning (artificial intelligence), motion estimation,
Video codecs
BibRef
Cheng, Z.X.[Zheng-Xue],
Sun, H.[Heming],
Takeuchi, M.[Masaru],
Katto, J.[Jiro],
Learning Image and Video Compression Through Spatial-Temporal Energy
Compaction,
CVPR19(10063-10072).
IEEE DOI
2002
BibRef
Lu, G.[Guo],
Ouyang, W.L.[Wan-Li],
Xu, D.[Dong],
Zhang, X.Y.[Xiao-Yun],
Cai, C.L.[Chun-Lei],
Gao, Z.Y.[Zhi-Yong],
DVC: An End-To-End Deep Video Compression Framework,
CVPR19(10998-11007).
IEEE DOI
2002
BibRef
Westland, N.,
Dias, A.S.,
Mrak, M.,
Decision Trees for Complexity Reduction in Video Compression,
ICIP19(2666-2670)
IEEE DOI
1910
Video Coding, Complexity Reduction, Machine Learning, Decision Trees
BibRef
Wang, J.,
Tao, X.,
Xu, M.,
Lu, J.,
Semantic Perceptual Image Compression with a Laplacian Pyramid of
Convolutional Networks,
ICIP19(699-703)
IEEE DOI
1910
image compression, deep learning, Laplacian pyramid,
adversarial network, perceptual loss
BibRef
Su, H.,
Tsai, C.,
Wang, Y.,
Xu, Y.,
Machine Learning Accelerated Partition Search for Video Encoding,
ICIP19(2661-2665)
IEEE DOI
1910
Video Coding, Machine Learning, Partition Search, Encoding Speedup, VP9
BibRef
Ho, Y.H.[Yung-Han],
Cho, C.Y.[Chuan-Yuan],
Peng, W.H.[Wen-Hsiao],
Deep Reinforcement Learning for Video Prediction,
ICIP19(604-608)
IEEE DOI
1910
Reinforcement learning, deep video prediction
BibRef
Kumar, S.[Saurabh],
Chaudhuri, S.[Subhasis],
Banerjee, B.[Biplab],
Ali, F.[Feroz],
Onboard Hyperspectral Image Compression Using Compressed Sensing and
Deep Learning,
CVUAV18(II:30-42).
Springer DOI
1905
BibRef
Nakanishi, K.M.[Ken M.],
Maeda, S.I.[Shin-Ichi],
Miyato, T.[Takeru],
Okanohara, D.[Daisuke],
Neural Multi-scale Image Compression,
ACCV18(VI:718-732).
Springer DOI
1906
consists of two networks: multi-scale lossy autoencoder
and parallel multi-scale lossless coder.
BibRef
He, X.Y.[Xiang-Yu],
Cheng, J.[Jian],
Learning Compression from Limited Unlabeled Data,
ECCV18(I: 778-795).
Springer DOI
1810
BibRef
Xu, K.[Kai],
Ren, F.[Fengbo],
CSVideoNet: A Real-Time End-to-End Learning Framework for
High-Frame-Rate Video Compressive Sensing,
WACV18(1680-1688)
IEEE DOI
1806
cameras, compressed sensing, data compression, decoding,
image reconstruction, image resolution,
Streaming media
BibRef
Chen, T.[Tong],
Liu, H.J.[Hao-Jie],
Shen, Q.[Qiu],
Yue, T.[Tao],
Cao, X.[Xun],
Ma, Z.[Zhan],
DeepCoder: A deep neural network based video compression,
VCIP17(1-4)
IEEE DOI
1804
Huffman codes, convolution, data compression,
feedforward neural nets, video coding,
video compression
BibRef
Pavez, E.,
Ortega, A.,
Mukherjee, D.,
Learning separable transforms by inverse covariance estimation,
ICIP17(285-289)
IEEE DOI
1803
Covariance matrices, Discrete cosine transforms, Encoding,
Estimation, Image coding, video coding
BibRef
Shen, H.,
Pan, W.D.[W. David],
Predictive lossless compression of regions of interest in
hyperspectral image via Maximum Correntropy Criterion based Least
Mean Square learning,
ICIP16(2182-2186)
IEEE DOI
1610
Data communication
BibRef
Quijas, J.,
Fuentes, O.,
Removing JPEG blocking artifacts using machine learning,
Southwest14(77-80)
IEEE DOI
1406
data compression
BibRef
Zhan, X.[Xin],
Zhang, R.[Rong],
Yin, D.[Dong],
Hu, A.Z.[An-Zhou],
Hu, W.[Wenlong],
Remote sensing image compression based on double-sparsity dictionary
learning and universal trellis coded quantization,
ICIP13(1665-1669)
IEEE DOI
1402
Dictionary learning
BibRef
Sun, X.Y.[Xiao-Yan],
Wu, F.[Feng],
Classified patch learning for spatially scalable video coding,
ICIP09(2301-2304).
IEEE DOI
0911
BibRef
He, X.F.[Xiao-Fei],
Ji, M.[Ming],
Bao, H.J.[Hu-Jun],
A unified active and semi-supervised learning framework for image
compression,
CVPR09(65-72).
IEEE DOI
0906
Learn which pixels predict the color for others.
BibRef
Lampert, C.H.[Christoph H.],
Machine Learning for Video Compression: Macroblock Mode Decision,
ICPR06(I: 936-940).
IEEE DOI
0609
BibRef
Simard, P.Y.,
Burges, C.J.C.,
Steinkraus, D.,
Malvar, H.S.,
Image compression with on-line and off-line learning,
ICIP03(II: 259-262).
IEEE DOI
0312
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Motion Coding, Evaluations, Surveys .