Coder selection for lossy compression of still images

DOI10.1016/S0031-3203(01)00211-4zbMath1006.68904OpenAlexW2007624831MaRDI QIDQ1860231

Yanyan Li

Publication date: 20 February 2003

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0031-3203(01)00211-4

zbMATH Keywords

lossy compressionachievable and non-achievable regionsBayesian error probabilitycoder selectionminimax Chernoff criterion

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10) Computing methodologies and applications (68U99)

Cites Work

• Unnamed Item
• On the concept of best achievable compression ratio for lossy image coding.
• Using models of feature perception in distortion measure guidance
• High-resolution source coding for non-difference distortion measures: multidimensional companding
• Asymptotic performance of vector quantizers with a perceptual distortion measure

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