Lossless image compression via multi-scanning and adaptive linear prediction

Haijiang Tang; Sei Ichiro Kamata; Kazuyuki Tsuneyoshi; Masa Aki Kobayashi

Lossless image compression via multi-scanning and adaptive linear prediction

Haijiang Tang, Sei Ichiro Kamata, Kazuyuki Tsuneyoshi, Masa Aki Kobayashi

Graduate School of Information, Production and Systems

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper presents an efficient lossless compression approach for gray scale images. The main contributions are 1) we divide the input image to blocks of pixels and use different scanning methods, we select the one that minimizes the prediction error for coding; 2) a new adaptive linear prediction is applied. Experiment results show that our method outperformed JPEG-LS 2∼10% in compression efficiency.

Original language	English
Pages	81-84
Number of pages	4
Publication status	Published - 2004 Dec 1
Event	2004 IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2004: SoC Design for Ubiquitous Information Technology - Tainan, Taiwan, Province of China Duration: 2004 Dec 6 → 2004 Dec 9

Conference

Conference	2004 IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2004: SoC Design for Ubiquitous Information Technology
Country/Territory	Taiwan, Province of China
City	Tainan
Period	04/12/6 → 04/12/9

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

Lossless image compression via multi-scanning and adaptive linear prediction. / Tang, Haijiang; Kamata, Sei Ichiro; Tsuneyoshi, Kazuyuki et al.
2004. 81-84 Paper presented at 2004 IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2004: SoC Design for Ubiquitous Information Technology, Tainan, Taiwan, Province of China.

Research output: Contribution to conference › Paper › peer-review

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PY - 2004/12/1

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AB - This paper presents an efficient lossless compression approach for gray scale images. The main contributions are 1) we divide the input image to blocks of pixels and use different scanning methods, we select the one that minimizes the prediction error for coding; 2) a new adaptive linear prediction is applied. Experiment results show that our method outperformed JPEG-LS 2∼10% in compression efficiency.

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Lossless image compression via multi-scanning and adaptive linear prediction

Abstract

Conference

ASJC Scopus subject areas

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