Content-based Fractal Image Compression System

With the application of fractal method in the computer technology, thetechnology of fractal image compression develops more and more perfectly. Fractalimage compression is a novelty image compression method; its compression ratiomay reach 10000 in the condition of manual intervention, and still has good visualeffect after decompression. In recent years, fractal image compression is also used tocompress a video image that has reached a visible result. In the traditional fractal video compression system, every frame of the givenvideo is compressed as an entity, and the characteristics and relations among videoobjects do not be taken into account when compressing. So the method cannot get ahigh compression ratio or sacrifice the quality of image in order to improve thecompression ratio. In fact, a video is composed of many image frames displayed atcertain speed. We can discover that in a small video the background does not oftenchange and only the foreground objects change by careful observation. In this paper,we combine the content-based method, which is brought forward in MPEG-4 with thefractal video compression method and give a new compression algorithm, thecontent-based fractal video compression method. In this algorithm, the foregroundobjects and the background are segmented and then compressed separately. Thebackgrounds in a small video are compressed only as a frame or some key frames.This algorithm greatly improves the compression ratio and ensures the quality ofimage at the same time. In developing the fractal video compression system, wedecompress the files that are encoded by the fractal compression method to imagesequences with RAW format, and display the sequences as sections of videos. So wecan intuitively compare the qualities of these images with original images. Moreoverwe adopt multi-thread technology to realize the synchronization between thedecompression and the playing in the fractal video compression system to improve theefficiency of the system. Experimental results show that the new method can obtain a much highercompression ratio compared to the original fractal video compression while thequalities of decompressed images keep the same. It will be a trend to usecontent-based video compression method in many place that backgrounds does notchange frequently such as USB pickup camera,video-phone,video on demand,videoconference system,numeric monitor system and so on.