Research On Optimized Coding Algorithm Based On The Standard Of JPEG2000

JPEG2000 is the new standard for the compression of still image established by the International Organization for Standardization (ISO) and the International Telecommunications Union (ITU). Compared with the former standards, JPEG2000 provides a set of advantages, such as superior low bit-rate performance, excellent progressive transmission by pixel accuracy and resolution and Region of Interests coding. It has a great variety of applications such as Internet, digital cameras, wireless communication, medical images. But the compression system of JPEG2000 is complex and needs much time for coding, which is not suitable for the high real-time system. Therefore, this dissertation aims at finding a solution to speed up coding with the similar compression performance.It is summarized as follows:①Based on full analysis of the core algorithm(EBCOT) in JPEG2000, it is found that the block coding within the core algorithm not only determines the compression performance of the whole system, but also occupies the time over 50 percent of the whole compression process.②Through full research on block coding, a coding feature is found that the three coding passes of block coding have different need-to-be-coded pixels. Based on this feature and the analysis of wavelet transform coefficients, an improved algorithm is proposed that can scan the higher bit plane in high frequency subbands(HL1,LH1,HH1) once and remove the Cleanup pass in lower bit plane.③A coding scheme of the improved algorithm is designed.④Based on the basic encoder/decoder system in JPEG2000 standard, within the development environment of Microsoft Visual C++6.0, the dissertation introduces the oriented object programmable idea, fabricates the basic encoder/decoder system, realizes the lossy and lossless compression of BMP grey still images by using the improved algorithm proposed in this dissertation and the standard algorithm in JPEG2000.Experiment of results show that the improved algorithm not only can reduce the coding time but also can slightly gain better lossless performance for still images. The improved algorithm is especially suitable for the real-time transmission image system.