A line-based lossless backward coding of wavelet trees (BCWT) and BCWT improvements for application
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Image compression has been developed through many years in order to approach the lower limit of compression ratio bounded by the entropy at the lowest possible system cost. Compression techniques such as JPEG, JPEG-LS and JPEG2000 were accepted as the International Compression Standards for continuous-tone images because of their excellent performance. In 2009, JPEG-XR was announced a a new image standard for lossy and lossless image compression. However, because ofthe compatibility issues such as its non- compatibility with previous standards or non-Microsoft products, JPEG-XR are not broadly employed. The previous standards are still employed for both lossy and lossless image compression. Wavelet-based codecs such as JPEG2000 provide abundant functionalities and excellent compression efficiency compared to other codecs but with more complexity. A wavelet-based algorithm, BCWT, has been developed in order to offer very low complexity while still providing the excellent compression efficiency and functionalities found in JPEG2000. It provides excellent performance, but several limitations hinder its practical application. In order to solve the limitations of the BCWT application, in this dissertation, a ‘set to zeros’ method and a ‘zero tree detection’ algorithm are proposed and incorporated in the BCWT algorithm, which greatly enhance the compression ratio while reserving the algorithm’s advantages without significantly increasing its complexities. An efficient line-based lossless BCWT with very low computational cost is proposed to extensively meet the lossless requirements for specific occasions. For further improvement of the compression ratio, statistical models are investigated so that the adaptive arithmetic coding technique can be effectively applied to the output bit-stream. Tests and analysis results show that the improved BCWT algorithm consumes less memory and computational resources and obtain higher compression ratio without significant increase of the system complexity as compared to the original BCWT. The improved BCWT algorithm and the proposed lossless version have been successfully applied to industrial embedded applications.