NDLI: A switching predictor for lossless image coding

Content Provider	IEEE Xplore Digital Library
Author	Lih-Jen Kau Yuan-Pei Lin
Copyright Year	2003
Description	Author affiliation: Dept. Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Lih-Jen Kau; Yuan-Pei Lin)
Abstract	In this paper, we propose a switching adaptive predictor (SWAP) with automatic context modeling for lossless image coding. In the SWAP system, two predictors are used. For areas with edges, estimates of coding pixels are obtained using texture context matching (TCM). For all other areas, an adaptive neural predictor (ANP) is used. The SWAP encoder switches between the two predictors ANP and TCM depending on the neighborhood of the coding pixel. The switching predictor allows statistical redundancy to be removed effectively. On the other hand, it is known that prediction can be further refined using error compensation. For this, we propose the use of a modified fuzzy clustering, which leads to a modeling of errors that adapts itself to the input statistics. Experiments show that the proposed context clustering is very useful in modeling error for prediction refinement. Comparisons of the proposed system to existing state-of-the-art predictive coders will be given to demonstrate its coding efficiency.
Sponsorship	Syst., Man & Cybernetics Soc. IEEE
Starting Page	228
Ending Page	233
File Size	496408
Page Count	6
File Format	PDF
ISBN	0780379527
ISSN	1062922X
DOI	10.1109/ICSMC.2003.1243820
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image coding Context modeling Neural networks Histograms Switches Predictive models Automatic control Programmable control Adaptive control Redundancy
Content Type	Text
Resource Type	Article

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