Medical image compression based on subband information statistic model

Li-bao Zhang

doi:10.1117/12.755621

29 November 2007 Medical image compression based on subband information statistic model

Li-bao Zhang

Proceedings Volume 6833, Electronic Imaging and Multimedia Technology V; 683326 (2007) https://doi.org/10.1117/12.755621
Event: Photonics Asia 2007, 2007, Beijing, China

Abstract

The IWT (Integer Wavelet Transform) can achieve genuine lossless image compression and allow both lossy and lossless compression using a single bit-stream. However, using the IWT instead of the DWT (Discrete Wavelet Transform) will degrade the performances of the lossy compression because the filter structure of IWT and the nonlinear rounding operation. In this paper, a new integer wavelet decomposition scheme is proposed based on subband local information statistic model for the medical images. The high frequency subbands can be decomposed again according to the statistic results of the subband coefficient entropies. The results of several experiments for the medical images presented in this paper demonstrate the importance subband information statistic in the integer wavelet decomposition. Furthermore, this paper shows that appropriate subband local information statistic model improves the performance of compression algorithm after the multilevel subband decomposition is performed. So we expect this idea is valuable for future research on medical image coding.

Citation Download Citation

Li-bao Zhang "Medical image compression based on subband information statistic model", Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 683326 (29 November 2007); https://doi.org/10.1117/12.755621

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