Study Based On Medical Image Compression Method

With the development of image processing and computer technologies, the digital image technology is increasing widely applied in the medical image areas, such as X-ray, CT, MRI, CR, DSA and US. At the other hand, PACS(Picture Archival and Communication System) and its application which basing on Computer network develop unceasing, and the amount of image data is vast. In the light of the characterisuc "May not lose any detail when compressing and encode with the medical image", this thesis revolves round the image compression and encoding to do the research.In this thesis, we present a image encode/decode compression system that synthesizes the lifting wavelet transform(SGWT) , SPIHT(Set Partitioning In Hierarchical Trees) algorithm and adaptive arithmetic coding., and simulate with the programs of VC++6.0. After comparing the original image statistical characteristic and histogram feature, we modify the encode/decode scheme. We amend the SPIHT algorithm in our scheme to decrease the run time, and increase the image compress ratio by reconstructing the code bits before the adaptive arithmetic codes. Based on analyzing and comparing the constringent performance of CDF(2,2) and FBI9-7 wavelet, we verify that "there is no wavelet that consistently performs better than all the other wavelets on all the test images." We analyze the adaptive arithmetic coding efficiency when choosing different threshold values, and different images in SPIHT algorithm Efficiency, and draw a conclusion that "There are straight forward relations between the coding efficiency of SPIHT algorithm and the number of zero in wavelet factor after lifting wavelet transform. The more large the number of zero are, the more compression effect of SPIHT algorithm is good." This system has a better effect on lossless and little lossy compression. The study indicates that the method make full use of the medical image statistical characteristics, the method achieves upper compress ratio, lesser spatial and time complex. Using progressive transmission will attain the appointed compress ratio and PSNR. For typical medical images (X-ray image, CT image, MRI image) storage, transfer and search, this system is sufficiently valid.