R-D Optimization Based Progressive Coding for JPEG

• Main Authors: Bau-Jing Tong, 童寶靖
• Other Authors: Tzone-I Wang
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/94808914281612925300

碩士 === 國立成功大學 === 工程科學系碩博士班 === 94 === JPEG (Joint Photographic Experts Group) is an ISO/IEC group of experts that develops and maintains standards for a suite of compression algorithms for computer image files. It is now regarded as a digital image compression standard of the International Standardization Organization (ISO) and the International Telegraph and Telephone Consultative Committee (CCITT). JPEG is mainly used in static image compression. It is a standard of lossy coding that uses discrete cosine transform (DCT) and quantizer to remove unimportant part, to retain important information, and to achieve the goal of high compression rate. Although the image will be distorted after JPEG processing, the distortion can be controlled by some parameters. Generally speaking, when you compress 5% ~ 15% off an original image, JPEG algorithm can still guarantee its suitable image quality, and this is some of the general lossless compression standard can not achieve. The JPEG image format is commonly used in daily life, for example in the internet web pages or in digital cameras. Although compression reduces the quality of images, it enables them to be stored or transmitted easier. This thesis proposes an algorithm that adaptively adjusts compression parameters according to data storage utilization. The algorithm acquires importance of every compressed data from frequency domain. When fewer images are stored, all the compressed data are store and the quality of all stored images is close to lossless compression. When the number of images increases, the algorithm dynamically adjusts storage space assignment according to the importance of each data. Meanwhile, it can smooth down the variation of quality among images and obtains better compression efficiency according to the rate-distortion theory. The experiments show that the quality variation and the compression efficiency are obviously improved when compared with standard JPEG compression.