JPEG Artifacts Reduction via Deep Convolutional Sparse Coding

To effectively reduce JPEG compression artifacts, we propose a deep convolutional sparse coding (DCSC) network architecture. We design our DCSC in the framework of classic learned iterative shrinkage-threshold algorithm. To focus on recognizing and separating artifacts only, we sparsely code the fea...

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Bibliographic Details

Published in:	Proceedings / IEEE International Conference on Computer Vision pp. 2501 - 2510
Main Authors:	Fu, Xueyang, Zha, Zheng-Jun, Wu, Feng, Ding, Xinghao, Paisley, John
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2019
Subjects:	Convolution Convolutional codes Encoding Feature extraction Image coding Task analysis Transform coding
ISSN:	2380-7504
Online Access:	Get full text
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