Presentation 2009-10-15
A lossless coding for still image of HDTV using adaptive liner prediction
Yuya YAMAGUCHI, Takashi OTSUKI, Ken-ichi IWATA, Shuichi ITOH,
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Abstract(in English) Lossless image compression is needed in the areas of medical imaging, high-definition image analysis and archives for art. Therefore, this paper presents a lossless image compression method for one frame of high-definition television (HDTV). We apply an adaptive liner prediction, and then the sequence of prediction errors is encoded by entropy coding. We divide an image into small blocks and classify them into some classes each of which corresponds to one MMSE linear predictor. Repeating classification of the blocks and rebuilding of the predictors until the prediction MSE converges, we get the optimal set of linear predictors for given image. In this paper, we consider the influence of the context length and the number of the linear predictors on compression ratio and processing time.
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Keyword(in English) high-definition television (HDTV) / lossless image compression / linear predictors / classified adaptive prediction
Paper # SIP2009-62,IE2009-87
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Committee IE
Conference Date 2009/10/8(1days)
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Paper Information
Registration To Image Engineering (IE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A lossless coding for still image of HDTV using adaptive liner prediction
Sub Title (in English)
Keyword(1) high-definition television (HDTV)
Keyword(2) lossless image compression
Keyword(3) linear predictors
Keyword(4) classified adaptive prediction
1st Author's Name Yuya YAMAGUCHI
1st Author's Affiliation Graduate School of Science and Engineering, Yamagata University()
2nd Author's Name Takashi OTSUKI
2nd Author's Affiliation Graduate School of Science and Engineering, Yamagata University
3rd Author's Name Ken-ichi IWATA
3rd Author's Affiliation Graduate School of Engineering, University of Fukui
4th Author's Name Shuichi ITOH
4th Author's Affiliation The University of Electro-Communications
Date 2009-10-15
Paper # SIP2009-62,IE2009-87
Volume (vol) vol.109
Number (no) 227
Page pp.pp.-
#Pages 6
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