Image Compression Method Based on Generalized Finite Automata
In this paper, we introduce an approach to compress gray image using deterministic Generalized Finite Automata (GFA). By detecting the self-similarity inside an input digitized gray image, a GFA can be constructed to describe the image. The decode algorithm can restore the image from the deterministic Generalized Finite Automata efficiently. This method has a smaller number of states than an equivalent classical finite automaton. Meanwhile it also has an advantage of higher compression without further degradation of quality.
Xiaohu Ma Huanqin Chen
School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006
国际会议
2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
镇江
英文
1688-1692
2008-07-07（万方平台首次上网日期，不代表论文的发表时间）