Finite State Discrete Cosine Transform for Image Compression

• Main Authors: Yung-Gi Wu, 吳永基
• Other Authors: Shen-Chuan Tai
• Format: Others
• Language: en_US
• Published: 1994
• Online Access: http://ndltd.ncl.edu.tw/handle/68322478679918275389

碩士 === 國立成功大學 === 電機工程研究所 === 82 === In this thesis,a new image compression method is devised. Discrete Cosine Transform is the kernel of the compressor. The new technique classifies the image subblock into eights classes by their characteristics which can be got from the transfomed domain.Four edge classes,three texture classes ,one smooth class.This kind of classification is called Three Model Classification.As to the overhead of classification ,finite state concept is used to reduce the overhead by predicting the current block's class from the previously blocks. In order to promote the correct ratio of prediction,edge orientation should be considered.We exploit the relationship between the transformed domain and edge orientation.As we know, the smooth regions occupy most part of a natual images.Larger coding size can get higher compression ratio in the smooth regions. But this will sacrifice the quality of complicated regions.In order to solve this deficiency.We devised a variable block coding size algorithm.The edge blocks use the fixed 8*8 block to keep the detailed parts and the variable block size segmentation scheme is applied to texture and smooth regions. The new segmentation method is called "class driven segmentation" The overhead of the segmention is zero. The simulation results show good quality for the decoded images.