With the ever increasing demand for images, sound, video sequences, computer animations and volume visualization, data compression remains a critical issue regarding the cost of data storage and transmission times. Clearly, compression is necessary. Various compression methods have been proposed in recent years using different techniques to achieve high compression ratios. All these methods share the same characteristic of being approximate, i.e. the compressed images will be approximations of the originals. While JPEG currently provides the industry standard for still image compression there is ongoing research in alternative methods. Fractal image compression is one of them. JPEG can be termed symmetric in the sense that the encoding and decoding phases require about the same number of operations. On the contrary, fractal image compression is asymmetric, requiring long encoding times while allowing fast decoding. Thus, the method seems to be most applicable where a large number of pre-encoded images have to be decoded quickly(multimedia, image-archiving, Video-On-Demand). Because of this wide applicable area and long computation times, fast decoder is needed.
Based on the Modified Recursive Decoding Algorithm(MRDA) which reduces the number of iterations and hardware cost, I designed and implemented the Fractal Transform Processor(Decoder) with 0.6 micron N-Well CMOS technology on 5mmx5mm silicon area. It decodes 2-D quadtree partitioned fractal image in real time. The implemented decoder have the features that RAM size is reduced by 50% and the decoding speed to get final attractor (reconstructed image) is improved by 50%, compared with conventional method using Classical Recursive Decoding Algorithms(CRDA). And It can produce 76 image frames per second.
