NDLI: Classification and blending prediction for lossless image compression

Content Provider	IEEE Xplore Digital Library
Author	Knezovic, J. Kovac, M. Mlinaric, H.
Copyright Year	2006
Description	Author affiliation: Fac. of Electr. Eng. & Comput., Zagreb Univ. (Knezovic, J.; Kovac, M.; Mlinaric, H.)
Abstract	In this paper we propose a new adaptive prediction scheme based on the blending of multiple static predictors on a dynamically classified causal context of neighboring pixels. The idea of predictor blends is further expanded through the determination of blending context that changes its shape on a pixel-by-pixel basis using a simple classification technique, thus allowing the modeling of more complex image structures such as nontrivially oriented edges, the periodicity and the coarseness of textures. Typical natural images are characterized as being composed of image regions with different local properties. Proposed predictor estimates those properties around the currently unknown pixel and adjusts itself so that the presence of detected properties affects the way final prediction is made
Sponsorship	IEEE Region 8 IEEE Spain Sect
Starting Page	486
Ending Page	489
File Size	204133
Page Count	4
File Format	PDF
ISBN	1424400872
DOI	10.1109/MELCON.2006.1653144
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-05-16
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image coding Pixel Context modeling Predictive models Image edge detection Entropy Predictive coding Redundancy Probability Gray-scale
Content Type	Text
Resource Type	Article

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