Non-uniform image compression using a biologically motivated selective attention model

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We propose a new non-uniform image compression algorithm using a biologically motivated selective attention model for the effective storage and transmission of natural images. The proposed selective attention model, which uses a bottom-up saliency map (SM) together with top-down reinforcement and inhibition, can generate a scan path that contains plausible interesting objects in a natural scene. The proposed non-uniform image compression method uses the SM results of the proposed selective attention model, which compresses the selected areas that are interesting and the uninteresting areas in a different way by a lossless coding algorithm and lossy compression, respectively. Experimental results show that the proposed non-uniform compression method provides a better peak signal-to-noise ratio (PSNR), but slightly decreases the compression ratio. (c) 2005 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2005-08
Language
English
Article Type
Article
Citation

NEUROCOMPUTING, v.67, pp.350 - 356

ISSN
0925-2312
DOI
10.1016/j.neucom.2004.12.010
URI
http://hdl.handle.net/10203/89727
Appears in Collection
CS-Journal Papers(저널논문)
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