Medical image compression based on subband information statistic model
| Autor: | Li-bao Zhang |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Discrete wavelet transform
Lossless compression business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Wavelet transform Data_CODINGANDINFORMATIONTHEORY Lossy compression Wavelet packet decomposition Wavelet Computer vision Artificial intelligence business Algorithm Mathematics Image compression Data compression |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.755621 |
| Popis: | 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.© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|