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Lossless video coding based on multi-frame example search and probability model optimization
Author(s): Koji Nemoto; Yusuke Kameda; Ichiro Matsuda; Susumu Itoh
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Paper Abstract

This paper describes a novel lossless video coding method that directly estimates a probability distribution of image values pel-by-pel. In the estimation process, several examples, i.e. a set of pels whose neighborhoods are similar to a local texture of the target pel to be encoded, are gathered from search windows located on an already encoded area of the current frame as well as those of the previous frames. Then the probability distribution is modeled as a weighted sum of the Gaussian functions whose center positions are given by the individual examples. Furthermore, model parameters that control shapes of the Gaussian functions are numerically optimized so that the resulting coding rate can be a minimum. Simulation results indicate that the coding performance can be improved by increasing the number of reference frames.

Paper Details

Date Published: 22 March 2019
PDF: 5 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104948 (22 March 2019); doi: 10.1117/12.2521541
Show Author Affiliations
Koji Nemoto, Tokyo Univ. of Science (Japan)
Yusuke Kameda, Tokyo Univ. of Science (Japan)
Ichiro Matsuda, Tokyo Univ. of Science (Japan)
Susumu Itoh, Tokyo Univ. of Science (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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