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A JPEG decompression technique based on compressed sensing
Author(s): Chihiro Tsutake; Ryoya Yamada; Toshiyuki Yoshida
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Paper Abstract

Total-variation-minimization-based JPEG decompression is recognized as a promising technique for providing artifact-free images. Such a technique is typically accomplished in solving an optimization problem based on iterative methods. However, conventional decompression techniques sometimes exhibit over-smoothed regions in decompressed images by increasing iteration count. As a result, users are confused since an optimal iteration number is unknown for an arbitrarily given JPEG bitstream. To overcome the difficulty, we propose a new iterative JPEG decompression technique that combines a total variation minimization strategy with the so-called compressed sensing. In contrast to existing approaches, our technique always provides optimal decompression results, despite increasing iteration count. The experimental results indicate that the proposed technique is advantageous over conventional ones.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104935 (22 March 2019); doi: 10.1117/12.2521526
Show Author Affiliations
Chihiro Tsutake, Univ. of Fukui (Japan)
Ryoya Yamada, Univ. of Fukui (Japan)
Toshiyuki Yoshida, Univ. of Fukui (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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