A Fractal Video Compression Algorithm Based On Motion Compensation

Fractal image compression is a relatively recent image compression method. Its extension to a sequence of motion images is important in video compression applications. It reduces the redundancy of images by using the self-similarity properties of images, in other words, one part of an image can always be found using a method called collage coding. Although the compression process is very time consuming, the decompressing algorithm is very simple. So it is suitable for the situation of one encoding and many decoding, such as video on demand, archive compression. A video can be considered as many images displayed at a certain speed. It can be found that the neighboring images change little. Many video compression standards use motion compensation method to deal with the similarities of frames in a small video. Traditional fractal video compression system does not take into account this similarity solely, and the compression ratio is not very high. In this paper we use motion compensation to deal with the ration of image frames and put forward a new compression algorithm, which is called a fractal video compression algorithm based on motion compensation. Firstly, we division a video frames as I (Intra Pictures) frames and P (Predicted Pictures) frames. Secondly, I frames are compressed by the algorithm of fractal image compression separately. P frames are processed by using motion compensation to achieve the forecast coding, which compressed by the method of motion estimation to gain the motion errors of P frame and the front frame. The values of motion errors are small and very similar, so they can be compressed by the fractal video compression algorithm which is based on adaptive partition. Experimental results show that the new method can obtain a much higher compression ratio compared to the original fractal video compression and achieve higher qualities of decompressed images. In this paper, we also extend the gray video compression method to RGB color video. A color image can be divided as R, G, B three channel gray images. For every channel videos we use fractal video compression and motion compensation algorithm to compress. Experimental results show that this method can obtain a higher compression ratio for color video and achieve higher qualities of decompressed images.