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Proceedings Paper

Pel-adaptive lossless predictive coding based on image segmentation
Author(s): Takayuki Nakachi; Tatsuya Fujii; Junji Suzuki
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Paper Abstract

Lossless image coding that can recover original image from its compressed signal is required in the fields of medical imaging, fine arts, printing, and any applications demanding high image fidelity. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. In this method, prediction coefficients are fixed within the subdivided block-by-block image and cannot to be adopted to local statistics efficiently. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder at each block. In this paper, we propose an improved MAR coding method based on image segmentation. The proposed MAR predictor can be adapted to local statistics of image efficiently. This coding method does not need transmit side- information to the decoder at each pixel. The effectiveness of the proposed model is shown through experiments using SHD images.

Paper Details

Date Published: 28 December 1998
PDF: 12 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334645
Show Author Affiliations
Takayuki Nakachi, NTT Optical Network Systems Labs. (Japan)
Tatsuya Fujii, NTT Optical Network Systems Labs. (Japan)
Junji Suzuki, NTT Optical Network Systems Labs. (Japan)

Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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