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-In this paper, we survey some of the recent advances in lossless compression of continuoustone images. The modeling paradigms underlying the state-of-the-art algorithms, and the principles guiding their design, are discussed in a unified manner. The algorithms are described and experimentally compared.

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In the past years, there have been several improvements in lossless image compression. All the recently proposed state-of-the-art lossless Image compressors can be roughly divided into two categories: single and double-pass compressors. Linear prediction is rarely used in the first category, while TMW [7], a state-of-the-art double-pass image compressor, relies on linear prediction for its performance. We propose a single-pass adaptive algorithm that uses context classification and multiple linear predictors, locally optimized on a pixel-by-pixel basis. Locality is also exploited in the entropy coding of the prediction error. The results we obtained on a test set of several standard images are encouraging. On the average, our ALPC obtains a compression ratio comparable to CALIC [20] while improving on some images. © 2000 IEEE Publisher item Identifier S0018-9219(00)09992-8