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Especially in lossless image coding the obtainable compression ratio stronglydepends on the amount of noise included in the data as all noise has to becoded, too. Different approaches exist for lossless image coding. We analyzethe compression performance of three kinds of approaches, namely directentropy, predictive and wavelet-based coding. The results from our theoreticalmodel are compared to simulated results from standard algorithms that base onthe three approaches. As long as no clipping occurs with increasing noise morebits are needed for lossless compression. We will show that for very noisysignals it is more advantageous to directly use an entropy coder withoutadvanced preprocessing steps.

On the influence of clipping in lossless predictive and wavelet coding of noisy images