Zerotree Wavelet-based Medical Image Compression

The wide use of digital image technologies produced a great deal medical data, which challenged the image Archiving and Communication technologies. Medical image compressing is one way to solving it.The aim of medical image compression is transforming its information from one form to another, which can reduce its data stream. There are many medical image compression methods, in which wavelet image coding is one important aspect because its ability of multi-resolution, meanwhile, it can combine itself with sub-band coding and HVS(Human Vision System).There are many image compression methods based on wavelet analysis. The most typical of them is EZW(Embedded Zerotree Wavelet) algorithm, which was put forward by Shapiro in 1993 .But it has shortcomings, such as low efficiency, having not used the multi-resolution property of wavelet, and so forth. Therefore, this algorithm is not ideal. According to this, the author brought RLC(Run Length Coding) to EZW and improved the algorithm based on the analysis of EZW algorithm and its improved algorithms in existence. The author firstly code the image with EZW, then code the output of EZW using RLC, and finally code the stream of RLC with adaptive binary arithmetic method. The result showed that the combination of EZW and RLC is better than EZW in Compression Ration.The study of effective medical image compression algorithm is very important to PACS(Pictures Archiving and Communication System). It can save storage space and communication time, improve the efficiency of medical images management and using. Accordingly, serving the clinic diagnosis and treatment.