Abstract — Lempel-Ziv methods were original introduced to compress one-dimensional data (text, object codes, etc.) but recently they have been successfully used in image compression. Constantinescu and Storer in [6] introduced a single-pass vector quantization algorithm that, with no training or previous knowledge of the digital data was able to achieve better compression results with respect to the JPEG standard and had also important computational advantages. We review some of our recent work on LZ-based, single pass, adaptive algorithms for the compression of digital images, taking into account the theoretical optimality of these approach, and we experimentally analyze the behavior of this algorithm with respect to the local dictionary size and with respect to the compression of bi- level images

Dictionary Based Compression for Images

CARPENTIERI, Bruno
2012-01-01

Abstract

Abstract — Lempel-Ziv methods were original introduced to compress one-dimensional data (text, object codes, etc.) but recently they have been successfully used in image compression. Constantinescu and Storer in [6] introduced a single-pass vector quantization algorithm that, with no training or previous knowledge of the digital data was able to achieve better compression results with respect to the JPEG standard and had also important computational advantages. We review some of our recent work on LZ-based, single pass, adaptive algorithms for the compression of digital images, taking into account the theoretical optimality of these approach, and we experimentally analyze the behavior of this algorithm with respect to the local dictionary size and with respect to the compression of bi- level images
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4250095
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