基于固定码本的分形图像编码算法

ON THE ALGORITHM OF FRACTAL IMAGE CODING BASED ON FIXED CODEBOOK

传统的分形图像编码根据图像内部的跨尺度自相似性,求解压缩仿射变换,完成图像编码,这种来自于自身的编码码本不一定是最佳的,而且编码时间通常较长。根据图像之间存在着相似性,构造一个适应性更强的固定编码码本,其它任何图像分形编码的值域块只在这个固定码本中搜索其最佳匹配块,并且省去等距变换,此外,解码也无需迭代。实验结果表明,在图像质量略有下降情况下,该算法较基本分形图像编码算法显著地提高了编码和解码的速度,而且算法简单,容易实现。如果对这种固定码本加以更好的适应性改造,将会进一步提高解码图像的质量。

The traditional fractal image coding is based on the self-similarity across different scales of the image inside, solves the compression affine transformation and completes the image coding. The codebook from the image itself is not necessarily the best, and the encoding time is usually longer. According to the existence of similarities between the images, we construct an adaptable codebook in which the best matching block can only be searched for by the range block of any image fractal coding, and isometric transformation is omitted. In addition, there is no need to iterate the decoded image. Experimental results show that in the ease of a slight decrease in image quality, the algorithm has better performance than basic fractal image coding and improves the encoding and decoding speed, and the algorithm is simple and easy to implement. If the fixed codebook improves through a better adaptation, it will enhance the quality of the decoded image.