A SVM and SSIM Embedded Fast Fractal Image Compression Algorithm

• Main Authors: Shih, Tsung-nan, 施宗男
• Other Authors: Kung, Chih-hsien
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/34588530856173151385

碩士 === 長榮大學 === 資訊管理學系碩士班 === 99 === Fractal image compression (FIC) is promising both theoretically and practically. The encoding speed of the traditional full search method is a key factor rendering the fractal image compression unsuitable for real-time application. The primary objective of this research is to investigate the comprehensive coverage of the principles and techniques of fractal image compression, and describes the implementation of a pre-processing strategy that can reduce the full searching domain blocks by training the Support Vector Machine which could recognize the self-similar pattern feature to enhance the domain block searching efficiency. In this research, the novel image quality index (Structure Similarity, SSIM) and SVM based block property classifier employed for the fractal image compression is investigated.