Presentation 2023-02-21
[Special Talk] Study of Probability Modeling for Lossless Image Coding Using Example Search and Adaptive Prediction
Hiroki Kojima, Yasuyo Kita, Ichiro Matsuda,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Many efficient lossless image coding methods predict the next pel value to be coded from the pels already coded, and remove the spatial redundancy of the image signal by subtracting the predicted value from the pel value. After removing the redundancy, the prediction residual is entropy coded using a single-peak probability distribution that has a peak near 0. With this technique, it is expected that the coding efficiency will deteriorate at pels that are difficult to model with a unimodal distribution, such as edges where multiple pel values occur with equal probability. Therefore, we developed a method that directly entropy coding the pel value using a multi-peak probability distribution without converting the original image into a prediction residual. This method models the probability distribution for each pel based on image information collected by processing such as template matching and adaptive prediction in the encoded region, and achieves better coding efficiency than conventional methods by optimizing the parameters that control the shape of the distribution. In this talk, we will report on techniques that further improve the coding efficiency and reduce computational complexity by devising the definition of probability models and the optimization procedure of parameters.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Lossless image coding / Example search / Adaptive prediction / Probability model optimization
Paper # ITS2022-46,IE2022-63
Date of Issue 2023-02-14 (ITS, IE)

Conference Information
Committee IE / ITS / ITE-MMS / ITE-ME / ITE-AIT
Conference Date 2023/2/21(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Hokkaido Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English) Image Processing, etc.
Chair Kazuya Kodama(NII) / Masahiro Fujii(Utsunomiya Univ.) / Kenji Machida(NHK) / Hiroyuki Arai(Nippon Inst. of Tech.) / Hisaki Nate(Tokyo Polytechnic Univ.)
Vice Chair Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo) / Kohei Ohno(Meiji Univ.) / Naohisa Hashimoto(AIST) / / Shogo Muramatsu(Niigata Univ)
Secretary Hiroyuki Bandoh(KDDI Research) / Toshihiko Yamazaki(Nagoya Inst. of Tech.) / Kohei Ohno(Toyama Prefectural Univ.) / Naohisa Hashimoto(NIT, Tsuruoka College) / (Fukuoka Univ.) / Shogo Muramatsu(NHK) / (Hokkaido Univ.)
Assistant Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Taishi Swabe(NAIST) / Keiji Jimi(Gunma Univ.)

Paper Information
Registration To Technical Committee on Image Engineering / Technical Committee on Intelligent Transport Systems Technology / Technical Group on Multi-media Storage / Technical Group on Media Engineering / Technical Group on Artistic Image Technology
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Special Talk] Study of Probability Modeling for Lossless Image Coding Using Example Search and Adaptive Prediction
Sub Title (in English)
Keyword(1) Lossless image coding
Keyword(2) Example search
Keyword(3) Adaptive prediction
Keyword(4) Probability model optimization
1st Author's Name Hiroki Kojima
1st Author's Affiliation KDDI CORPORATION(KDDI)
2nd Author's Name Yasuyo Kita
2nd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
3rd Author's Name Ichiro Matsuda
3rd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
Date 2023-02-21
Paper # ITS2022-46,IE2022-63
Volume (vol) vol.122
Number (no) ITS-384,IE-385
Page pp.pp.25-25(ITS), pp.25-25(IE),
#Pages 1
Date of Issue 2023-02-14 (ITS, IE)