Learning Nonlinear Predictive Models for Lossless Image Compression
نویسندگان
چکیده
We describe a genetic programming system which learns nonlinear predictive models for lossless image compression. S-expressions which represent nonlinear predictive models are learned, and the error image is compressed using an adaptive Huffman encoder. We show that the proposed system is capable of achieving compression ratios superior to that of the best known lossless compression algorithms.
منابع مشابه
Evolving Nonlinear Predictive Models for Lossless Image Compression with Genetic Programming
We describe a genetic programming system which learns nonlinear predictive models for lossless image compression. Sexpressions which represent nonlinear predictive models are learned, and the error image is compressed using a Huffman encoder. We show that the proposed system is capable of achieving compression ratios superior to that of the best known lossless compression algorithms, although i...
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تاریخ انتشار 2000