Research On Embedded Wavelet Image Coding Algorithm And Application

With the rapid development of the Internet, image compression plays a vital role in the storage and transmission of multimedia information. Conventional DCT-based coding scheme will inevitably produce block artifacts and mosquito noise in the case of high compression ratio, which results in a seriously harming to the subjective quality of the reconstructed image. For the capability of multi-resolution analysis consistent with human visual system and the direction selectivity, wavelet transform has been widely used in the field of image compression. The promulgating of JPEG2000 indicates that wavelet transform has successfully replaced DCT and become a major transform tool of the new generation of image coding algorithm. Embedded wavelet image coding, taking the advantage of resolution scalable, quality scalable and strong error-resilient performance, has been an important research direction of image coding. But the current methods are still not able to take full use of all the statistical characteristics of wavelet coefficients, how to make better use of the variety of relevance of wavelet transform coefficients in order to effectively organize the wavelet coefficients, especially to combine wavelet transform with other techniques to further enhance the compression performance, are the main topics in the research of wavelet image coding.In this dissertation, the popular wavelet image coding algorithms are analyzed in detail, then embedded wavelet image coding algorithms are studied mainly from four aspect as follows.(1)The fractal based wavelet image coding algorithm was studied deeply. Aimed at the problem of too much time overhead for matching search of fractal image coding, a block based fractal searching tree structure was proposed, which reduced the searching range of domain pool effectively and improved the match precision. A self-adaptive way was adopted to partition range blocks according to the importance of wavelet coefficients in different sub-bands. Then seek for a group of compression affine transforms to make the IFS approximate to the given attractors, and at last carry out entropy coding to the fractal parameters obtained. The quality of reconstructed image is better than that of the existing algorithms, especially the PSNR increases significantly in medium and low bit-rate. (2)Considering the unbalance problem of fractal in coding and decoding, the wavelet image coding algorithm was studied further from the perspective of SVM. Basing on the wavelet transform, a tree structure suitable for SVM regression was constructed, and the distribution of significant coefficients in the tree was analyzed. Then a linear threshold selection method was proposed to make the distribution of coefficients involved in the regression tend to be uniform in order to facilitate the regression process. On that basis, a dynamic error parameter selection method was put forward according to the thresholds and the precision of the regression fitting was improved further. At last the support vectors and their weights are entropy coded. The algorithm is provided with embedded feature, and the compression ratio improved significantly.(3)Although better coding effect was achieved by combining with fractal and SVM, the wavelet transform is not the best or the most sparse in two dimensional image representation. So Contourlet transform based image coding algorithm was studied. Combine the wavelet transform with Contourlet to obtain non-redundant Contourlet transform, then perform visual weighting based on HVS to each sub-band. For that the direction decomposition of Contourlet do not consider the distribution characteristics of coefficients inside each sub-band, the changing situation of entropy with the direction number of sub-band decomposition was studied. Then an entropy based optimization algorithm of direction decomposition was presented and the local relevance inside each sub-band was enhanced. The SPECK algorithm was adopted to encode each sub-band decomposed through the optimized direction decomposition algorithm. Not only the PSNR of the reconstructed image is improved, but also the distortion for local texture is much less.(4)Core image compression using wavelet packet based EBCOT algorithm was studied. Considering that the texture feature is predominant in core images, wavelet packet decomposition was adopted to enhance the representation ability to high-frequency details. Due to the large amount of calculation of the rate-distortion method and the incapacity in representing texture information effectively of entropy method, a fractal dimension based optimal wavelet packet base selection method was proposed, in which the decomposition pattern is consistent with the direction feature of each sub-band. On this basis, use EBCOT algorithm to execute compression to core image, and a parallel pass scanning method was proposed to enhance the speed of EBCOT. The experimental results demonstrate that the compression ratio and the speed are both higher than JPEG2000.