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Image/Video Coding

IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER


This paper addresses the problem of image compression using
sparse representations. We propose a variant of autoencoder
called Stochastic Winner-Take-All Auto-Encoder
(SWTA AE). “Winner-Take-All” means that image patches
compete with one another when computing their sparse representation
and “Stochastic” indicates that a stochastic hyperparameter
rules this competition during training. Unlike
auto-encoders, SWTA AE performs variable rate image compression
for images of any size after a single training, which

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Authors:
Thierry Dumas, Aline Roumy, Christine Guillemot
Submitted On:
14 March 2017 - 10:35am
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[1] Thierry Dumas, Aline Roumy, Christine Guillemot, "IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1765. Accessed: Aug. 24, 2017.
@article{1765-17,
url = {http://sigport.org/1765},
author = {Thierry Dumas; Aline Roumy; Christine Guillemot },
publisher = {IEEE SigPort},
title = {IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER},
year = {2017} }
TY - EJOUR
T1 - IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER
AU - Thierry Dumas; Aline Roumy; Christine Guillemot
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1765
ER -
Thierry Dumas, Aline Roumy, Christine Guillemot. (2017). IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER. IEEE SigPort. http://sigport.org/1765
Thierry Dumas, Aline Roumy, Christine Guillemot, 2017. IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER. Available at: http://sigport.org/1765.
Thierry Dumas, Aline Roumy, Christine Guillemot. (2017). "IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER." Web.
1. Thierry Dumas, Aline Roumy, Christine Guillemot. IMAGE COMPRESSION WITH STOCHASTIC WINNER-TAKE-ALL AUTO-ENCODER [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1765

Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition


Existed inherent sparsity of natural images in some domains helps to reconstruct the signal with a lower number of measurements. To benefit from the sparsity, one should solve the reweighted $\ell_{1}$-norm minimization algorithms. Although, the existed reweighted $\ell_{1}$-norm minimization approaches work well for k-sparse signals, but, the performance of these methods for compressible signals are not competitive with unweighted one.

poster.pdf

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Authors:
Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar
Submitted On:
14 March 2017 - 5:40am
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[1] Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar, "Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1763. Accessed: Aug. 24, 2017.
@article{1763-17,
url = {http://sigport.org/1763},
author = {Niloufar Abaei; Seyed Hamid Safavi; Farah Torkamani-Azar },
publisher = {IEEE SigPort},
title = {Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition},
year = {2017} }
TY - EJOUR
T1 - Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition
AU - Niloufar Abaei; Seyed Hamid Safavi; Farah Torkamani-Azar
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1763
ER -
Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar. (2017). Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition. IEEE SigPort. http://sigport.org/1763
Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar, 2017. Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition. Available at: http://sigport.org/1763.
Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar. (2017). "Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition." Web.
1. Niloufar Abaei, Seyed Hamid Safavi, Farah Torkamani-Azar. Reweighted Block-Based Compressed Sensing Using Singular Value Decomposition [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1763

A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING


Recently, multidimensional signal reconstruction using a low number of measurements is of great interest. Therefore, an effective sampling scheme which should acquire the most information of signal using a low number of measurements is required. In this paper, we study a novel cube-based method for sampling and reconstruction of multidimensional signals. First, inspired by the block-based compressive sensing (BCS), we divide a group of pictures (GoP) in a video sequence into cubes. By this way, we can easily store the measurement matrix and also easily can generate the sparsifying basis.

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Authors:
Seyed Hamid Safavi, Farah Torkamani-Azar
Submitted On:
12 March 2017 - 11:44am
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[1] Seyed Hamid Safavi, Farah Torkamani-Azar, "A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1748. Accessed: Aug. 24, 2017.
@article{1748-17,
url = {http://sigport.org/1748},
author = {Seyed Hamid Safavi; Farah Torkamani-Azar },
publisher = {IEEE SigPort},
title = {A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING},
year = {2017} }
TY - EJOUR
T1 - A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING
AU - Seyed Hamid Safavi; Farah Torkamani-Azar
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1748
ER -
Seyed Hamid Safavi, Farah Torkamani-Azar. (2017). A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING. IEEE SigPort. http://sigport.org/1748
Seyed Hamid Safavi, Farah Torkamani-Azar, 2017. A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING. Available at: http://sigport.org/1748.
Seyed Hamid Safavi, Farah Torkamani-Azar. (2017). "A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING." Web.
1. Seyed Hamid Safavi, Farah Torkamani-Azar. A NOVEL ADAPTIVE WEIGHTED KRONECKER COMPRESSIVE SENSING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1748

Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation


Conventional pixel-domain block matching temporal (inter) prediction is suboptimal, since it ignores the underlying spatial correlation. Hence in our recent research we proposed transform domain temporal prediction (TDTP), wherein spatially de-correlated transform coefficients are individually predicted. Later we proposed extended block TDTP (EB-TDTP), which fully exploits spatial correlation around reference block boundaries. However, the transform domain temporal correlation exploited by (EB-)TDTP interferes with the frequency response of sub-pixel interpolation filters.

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Authors:
Tejaswi Nanjundaswamy, Kenneth Rose
Submitted On:
11 March 2017 - 12:06am
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[1] Tejaswi Nanjundaswamy, Kenneth Rose, "Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1742. Accessed: Aug. 24, 2017.
@article{1742-17,
url = {http://sigport.org/1742},
author = {Tejaswi Nanjundaswamy; Kenneth Rose },
publisher = {IEEE SigPort},
title = {Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation},
year = {2017} }
TY - EJOUR
T1 - Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation
AU - Tejaswi Nanjundaswamy; Kenneth Rose
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1742
ER -
Tejaswi Nanjundaswamy, Kenneth Rose. (2017). Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation. IEEE SigPort. http://sigport.org/1742
Tejaswi Nanjundaswamy, Kenneth Rose, 2017. Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation. Available at: http://sigport.org/1742.
Tejaswi Nanjundaswamy, Kenneth Rose. (2017). "Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation." Web.
1. Tejaswi Nanjundaswamy, Kenneth Rose. Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1742

Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards


Recent MPEG video compression standards are still block-based: blocks of pixels are sequentially coded using spatial or temporal prediction schemes. For each block, a vector of coding parameters has to be selected. In order to limit the complexity of this decision, independence between blocks is assumed, and coding parameters are locally optimized to maximize the coding efficiency. Few studies have investigated the benefits of inter-block dependencies consideration using Joint Rate-Distortion Optimization (JRDO), especially in Intra coding.

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Authors:
Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang
Submitted On:
15 March 2017 - 6:08am
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[1] Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang, "Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1735. Accessed: Aug. 24, 2017.
@article{1735-17,
url = {http://sigport.org/1735},
author = {Maxime Bichon; Julien Le Tanou; Michael Ropert; Wassim Hamidouche; Luce Morin; Lu Zhang },
publisher = {IEEE SigPort},
title = {Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards},
year = {2017} }
TY - EJOUR
T1 - Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards
AU - Maxime Bichon; Julien Le Tanou; Michael Ropert; Wassim Hamidouche; Luce Morin; Lu Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1735
ER -
Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang. (2017). Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards. IEEE SigPort. http://sigport.org/1735
Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang, 2017. Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards. Available at: http://sigport.org/1735.
Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang. (2017). "Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards." Web.
1. Maxime Bichon, Julien Le Tanou, Michael Ropert, Wassim Hamidouche, Luce Morin, Lu Zhang. Inter-Block Dependencies Consideration Applied to Intra Coding in H.264/AVC and HEVC standards [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1735

IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING

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Authors:
Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing
Submitted On:
3 March 2017 - 1:34am
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[1] Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing, "IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1603. Accessed: Aug. 24, 2017.
@article{1603-17,
url = {http://sigport.org/1603},
author = {Siwei Dong; Yaowei Wang; Yonghong Tian; Peiyin Xing },
publisher = {IEEE SigPort},
title = {IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING},
year = {2017} }
TY - EJOUR
T1 - IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING
AU - Siwei Dong; Yaowei Wang; Yonghong Tian; Peiyin Xing
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1603
ER -
Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing. (2017). IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING. IEEE SigPort. http://sigport.org/1603
Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing, 2017. IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING. Available at: http://sigport.org/1603.
Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing. (2017). "IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING." Web.
1. Siwei Dong, Yaowei Wang, Yonghong Tian, Peiyin Xing. IMPROVED ADVANCED MOTION VECTOR PREDICTION SCHEME FOR SURVEILLANCE VIDEO CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1603

A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC


With the quad-tree based coding structure and more flexible intra-modes, the coding efficiency provided by intra-technique in inter-frames of HEVC is much higher than the preceding standard H.264/AVC. However, the computing complexity is also significantly increased. Although only a few CUs are encoded as intra-mode in inter-frames finally, almost all CUs need to be checked all the intra-options to obtain the optimal mode, which may be in fact unnecessary.

ICASSP2017_TT.pdf

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Authors:
Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao
Submitted On:
1 March 2017 - 3:25am
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[1] Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao, "A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1535. Accessed: Aug. 24, 2017.
@article{1535-17,
url = {http://sigport.org/1535},
author = {Tingting Wang; Yangyang Men; Yihao Zhang; Hongyang Chao },
publisher = {IEEE SigPort},
title = {A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC},
year = {2017} }
TY - EJOUR
T1 - A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC
AU - Tingting Wang; Yangyang Men; Yihao Zhang; Hongyang Chao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1535
ER -
Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao. (2017). A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC. IEEE SigPort. http://sigport.org/1535
Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao, 2017. A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC. Available at: http://sigport.org/1535.
Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao. (2017). "A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC." Web.
1. Tingting Wang, Yangyang Men, Yihao Zhang, Hongyang Chao. A Fast Intra-Prediction Decision Algorithm in Inter-Frame based on a Novel Feature of HEVC [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1535

FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL

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Authors:
Yi Shan, En-hui Yang
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28 February 2017 - 4:43pm
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[1] Yi Shan, En-hui Yang, "FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1517. Accessed: Aug. 24, 2017.
@article{1517-17,
url = {http://sigport.org/1517},
author = {Yi Shan; En-hui Yang },
publisher = {IEEE SigPort},
title = {FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL},
year = {2017} }
TY - EJOUR
T1 - FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL
AU - Yi Shan; En-hui Yang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1517
ER -
Yi Shan, En-hui Yang. (2017). FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL. IEEE SigPort. http://sigport.org/1517
Yi Shan, En-hui Yang, 2017. FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL. Available at: http://sigport.org/1517.
Yi Shan, En-hui Yang. (2017). "FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL." Web.
1. Yi Shan, En-hui Yang. FAST HEVC INTRA CODING ALGORITHM BASED ON MACHINE LEARNING AND LAPLACIAN TRANSPARENT COMPOSITE MODEL [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1517

Image Compression via Multiple Learned Geometric Dictionaries

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Authors:
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu
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8 December 2016 - 8:37am
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[1] Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu, "Image Compression via Multiple Learned Geometric Dictionaries ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1421. Accessed: Aug. 24, 2017.
@article{1421-16,
url = {http://sigport.org/1421},
author = {Danlan Huang; Xiaoming Tao; Mai Xu; Shenghua Gao; and Jianhua Lu },
publisher = {IEEE SigPort},
title = {Image Compression via Multiple Learned Geometric Dictionaries },
year = {2016} }
TY - EJOUR
T1 - Image Compression via Multiple Learned Geometric Dictionaries
AU - Danlan Huang; Xiaoming Tao; Mai Xu; Shenghua Gao; and Jianhua Lu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1421
ER -
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. (2016). Image Compression via Multiple Learned Geometric Dictionaries . IEEE SigPort. http://sigport.org/1421
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu, 2016. Image Compression via Multiple Learned Geometric Dictionaries . Available at: http://sigport.org/1421.
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. (2016). "Image Compression via Multiple Learned Geometric Dictionaries ." Web.
1. Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. Image Compression via Multiple Learned Geometric Dictionaries [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1421

Image Compression via Multiple Learned Geometric Dictionaries

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Authors:
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu
Submitted On:
7 December 2016 - 10:34pm
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Danlan Huang presentation slides

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[1] Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu, "Image Compression via Multiple Learned Geometric Dictionaries ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1419. Accessed: Aug. 24, 2017.
@article{1419-16,
url = {http://sigport.org/1419},
author = {Danlan Huang; Xiaoming Tao; Mai Xu; Shenghua Gao; and Jianhua Lu },
publisher = {IEEE SigPort},
title = {Image Compression via Multiple Learned Geometric Dictionaries },
year = {2016} }
TY - EJOUR
T1 - Image Compression via Multiple Learned Geometric Dictionaries
AU - Danlan Huang; Xiaoming Tao; Mai Xu; Shenghua Gao; and Jianhua Lu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1419
ER -
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. (2016). Image Compression via Multiple Learned Geometric Dictionaries . IEEE SigPort. http://sigport.org/1419
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu, 2016. Image Compression via Multiple Learned Geometric Dictionaries . Available at: http://sigport.org/1419.
Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. (2016). "Image Compression via Multiple Learned Geometric Dictionaries ." Web.
1. Danlan Huang, Xiaoming Tao, Mai Xu, Shenghua Gao, and Jianhua Lu. Image Compression via Multiple Learned Geometric Dictionaries [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1419

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