Hybrid Fractal Image Compression Based on Graph Theory and Equilateral Triangle Segmentation

摘要

Fractal based digital image compression is a very specific technique in the field of color image compression. The method is best suited for irregular shape of image like snow bobs, clouds, flame of fire; tree leaves images, depending on the fact that parts of an image often resemble with other parts of the same image. Fractal coding has not been widely used because of its long encoding time and high computational complexity. This image compression has received much attention from the research community because of some desirable properties like resolution independence, fast decoding, and very competitive rate-distortion curves. Despite the advances made, the long computing times in the encoding phase still remain the main disadvantages of this technique. However, many solutions have been proposed for this problem, but there is not yet a standard for fractal coding. In this paper we proposed fractal coding based on equilateral triangle segmentation and apply graph-based image segmentation to fractal image compression, separating the initial image into many logic areas, and then encoding each area with fractal image compression method. Experimental results show that, compared with the typical approaches, proposed approach can accelerate the fractal coding speed on the premise of guaranteeing the decoded images quality. Proposed hybrid scheme incorporating fractal compression and speedup techniques have achieved high compression ratio compared to pure fractal compression.