Medical Image Coding Based On Wavelet

More and more researches focus on wavelet based image coding as the wavelet theory research proceeds in last decade. Under this background, my research is mainly about the development of novel wavelet based image coding schemes with special reference to medical images. In this thesis, several new medical image coding algorithms are put forward. The main contributions are as follows:1) Proposing a new EBOHT(Embedded Block Coding with Optimized Truncation of Hierarchical Trees) image coding algorithm. In this scheme, Wavelet coefficients are divided into many blocks according to its spatial position. For each block, the algorithm adopts a improved SPIHT which has a predictive procedure to exploit the correlation among the adjacent coefficients. Then a optimizing method based on rate-distortion curve is used to make reasonable bit-allocation among the blocks. By arranging the datum into blocks, EBOHT outperforms SPIHT with regard to error resilience and is easy to achieves Regions of Interest (ROI) coding of images.2) Proposing a new Wavelet Image Coding method based on Predictive Quadtree-split. This method hybridizes the intra-band and inter-band coding. Wavelet coefficients in same band are partitioned into many blocks, and the blocks split according to quadtree with the moving of bitplane. This kind of dynamic block spliting can overcome some shortcomings brought by fixed block size. At the same time, the algorithm introduces a predictive coding procedure to truncate the block and make the block's shape fit in with the actual image. A context based arithmetic coder is adopted in entropy coding, and four different sets of models are designed for the arithmetic coder. The experiment results show that the proposed algorithm provides better compressionratio compared with EZW, SPITH, JPEG2000, QT_L.3) Proposing two kinds of new fuzzy clustering algorithm. The first one gets the equivalent matrices by modifying the fuzzy consistent matrices directly. So it can avoid the expending of distance measures. The second one truncates the FC-Tree based on rate-distortion curve to get a optimal clustering. The objective and subjective evaluation shows that these two algorithms provide significant improvement compared to LBG.4) Proposing a new VQ compression scheme. The method realizes the embedded coding through MVQ and SPIHT like coding structure, the experiment results shows this scheme can get excellent performances when using the corresponding codebook for specified type of medical images.