Speeding up Fractal Image Compression Based on Local Extreme Points

In fractal image compression, the encoding step is computationally expensive and consumes longer time, which limits the workable applications of fractal image compression. Combining with the characteristics of fractal image encoding, this paper presents an improved image blocks classification method to speed up the encoding process. The classification features are the number and the positions of the local extreme points in row direction in an image block, and a three layers tree classifier which provides a stepwise precise classification is utilized. The comparative experiments results show the validity of presented approach in accelerating fractal encoding process and holding the quality of the reconstructed image, and show the presented approach with simple principle can classify the image blocks more accurately.