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Information-theoretic learning (MLR-INFO)

A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising


A learning-based framework for representation of domain-specific images is proposed where joint compression and denoising can be done using a VQ-based multi-layer network. While it learns to compress the images from a training set, the compression performance is very well generalized on images from a test set. Moreover, when fed with noisy versions of the test set, since it has priors from clean images, the network also efficiently denoises the test images during the reconstruction.

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Authors:
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov
Submitted On:
15 September 2017 - 10:56am
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Multi-layer image representation

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[1] Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov, "A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2138. Accessed: Nov. 22, 2017.
@article{2138-17,
url = {http://sigport.org/2138},
author = {Sohrab Ferdowsi; Slava Voloshynovskiy; Dimche Kostadinov },
publisher = {IEEE SigPort},
title = {A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising},
year = {2017} }
TY - EJOUR
T1 - A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising
AU - Sohrab Ferdowsi; Slava Voloshynovskiy; Dimche Kostadinov
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2138
ER -
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov. (2017). A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising. IEEE SigPort. http://sigport.org/2138
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov, 2017. A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising. Available at: http://sigport.org/2138.
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov. (2017). "A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising." Web.
1. Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov. A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2138

AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING


Screen content has different characteristics compared with natural content captured by cameras. To achieve more efficient compression, some new coding tools have been developed in the High Efficiency Video Coding (HEVC) Screen Content Coding (SCC) Extension, which also increase the computational complexity of encoder. In this paper, complexity analysis are first conducted to explore the distribution of complexities.

Paper Details

Authors:
Liquan Shen, Ping An
Submitted On:
15 September 2017 - 5:05am
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ICIP2017 poster of paper #1561

(14 downloads)

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[1] Liquan Shen, Ping An, "AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2114. Accessed: Nov. 22, 2017.
@article{2114-17,
url = {http://sigport.org/2114},
author = {Liquan Shen; Ping An },
publisher = {IEEE SigPort},
title = {AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING},
year = {2017} }
TY - EJOUR
T1 - AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING
AU - Liquan Shen; Ping An
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2114
ER -
Liquan Shen, Ping An. (2017). AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING. IEEE SigPort. http://sigport.org/2114
Liquan Shen, Ping An, 2017. AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING. Available at: http://sigport.org/2114.
Liquan Shen, Ping An. (2017). "AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING." Web.
1. Liquan Shen, Ping An. AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2114

AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING


Screen content has different characteristics compared with natural content captured by cameras. To achieve more efficient compression, some new coding tools have been developed in the High Efficiency Video Coding (HEVC) Screen Content Coding (SCC) Extension, which also increase the computational complexity of encoder. In this paper, complexity analysis are first conducted to explore the distribution of complexities.

Paper Details

Authors:
Liquan Shen, Ping An
Submitted On:
15 September 2017 - 5:05am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP 2017 paper ID: 1561

(17 downloads)

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[1] Liquan Shen, Ping An, "AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2112. Accessed: Nov. 22, 2017.
@article{2112-17,
url = {http://sigport.org/2112},
author = {Liquan Shen; Ping An },
publisher = {IEEE SigPort},
title = {AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING},
year = {2017} }
TY - EJOUR
T1 - AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING
AU - Liquan Shen; Ping An
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2112
ER -
Liquan Shen, Ping An. (2017). AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING. IEEE SigPort. http://sigport.org/2112
Liquan Shen, Ping An, 2017. AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING. Available at: http://sigport.org/2112.
Liquan Shen, Ping An. (2017). "AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING." Web.
1. Liquan Shen, Ping An. AN EFFICIENT INTRA CODING ALGORITHM BASED ON STATISTICAL LEARNING FOR SCREEN CONTENT CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2112

INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION


This is an overview poster of the paper INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION.

Paper Details

Authors:
Zheng Cao, Jose C. Principe, Bing Ouyang
Submitted On:
12 March 2016 - 1:40pm
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zheng_icassp16_2.pdf

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[1] Zheng Cao, Jose C. Principe, Bing Ouyang, "INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/646. Accessed: Nov. 22, 2017.
@article{646-16,
url = {http://sigport.org/646},
author = {Zheng Cao; Jose C. Principe; Bing Ouyang },
publisher = {IEEE SigPort},
title = {INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION},
year = {2016} }
TY - EJOUR
T1 - INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION
AU - Zheng Cao; Jose C. Principe; Bing Ouyang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/646
ER -
Zheng Cao, Jose C. Principe, Bing Ouyang. (2016). INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION. IEEE SigPort. http://sigport.org/646
Zheng Cao, Jose C. Principe, Bing Ouyang, 2016. INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION. Available at: http://sigport.org/646.
Zheng Cao, Jose C. Principe, Bing Ouyang. (2016). "INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION." Web.
1. Zheng Cao, Jose C. Principe, Bing Ouyang. INFORMATION POINT SET REGISTRATION FOR SHAPE RECOGNITION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/646