Transform domain LMS-based adaptive prediction for lossless image coding

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摘要

This paper is concerned with adaptive prediction for lossless image coding. A new predictor is proposed. This predictor involves two major steps: constructing a good predictor for each pixel using the transform domain LMS algorithm and adaptively combining it with a set of fixed predictors. The first step is targeting areas where simple predictors do not perform well, while the second step is an effective method to reduce the modelling costs associated with the uncertainty of the models. When a context-based arithmetic encoder is used to encode the prediction error, the compression performance of the proposed algorithm is better than or comparable to that of other published algorithms.

论文关键词:Lossless image compression,Adaptive prediction,Transform domain LMS algorithm,Context-based entropy coding

论文评审过程:Received 15 June 2000, Revised 12 June 2001, Accepted 10 July 2001, Available online 2 January 2002.

论文官网地址:https://doi.org/10.1016/S0923-5965(01)00019-4