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1 引言自80年代中后期,Barnsley等人提出分形图像压缩的概念以来,分形图像编码作为一种新的具有高压缩比潜力的图像编码方法,越来越受到广泛的关注。分形图像编码的数学基础是迭代函数系统(IFS)和拼贴定理。基于迭代函数系统的基本的自动分形图像编码首先将原始图像分割成不相互重叠的小方块,然后对各个小方块构造迭代函数系统,即对每个小方块分别编码。然而,当图像的压缩比提高时,这种基于块的分形图像编码方法会引起图像的信噪比下降,并且一般来说,图像的主观质量也随之降低。主要表现为恢复图像中相邻图像块的边界衔接不连续,即通常所说的存在块状效应。
1 Introduction Since the mid-1980s, Barnsley et al. Put forward the concept of fractal image compression, fractal image coding has drawn more and more attention as a new image coding method with high compression ratio potential. The mathematical basis for fractal image coding is the Iterative Function System (IFS) and the collage theorem. The basic automatic fractal image coding based on the iterative function system firstly divides the original image into small squares that do not overlap with each other, and then constructs an iterative function system for each small square, ie encodes each small square separately. However, when the image compression ratio is increased, this block-based fractal image coding method will cause the image signal to noise ratio to decline, and in general, the subjective quality of the image will also be reduced. Mainly for the adjacent image blocks in the restoration image, the boundary connection discontinuity, which is commonly referred to as the block effect.