Data compression-the process of encoding data to reduce their storage requirements

Data compression-the process of encoding data to reduce their storage requirements-increases the effctive capacity of both storage media and communication channels.Today,data compression techniques are being applied with striking succss in such diverse areas as written text, computer code, scientific data, graphics, maps, speech and video, among others. While JPEG is becoming the industry standard for image compression technology, there is ongoing research in alternative methods. Fractal image compression is one of these new developments. Since the conception of fractal image compression by Bansley around 1987, the reasch on this topic has experenced a rapid growth. There are two types of mothod. The first is devoted to works using the basic IFS method; the second coside local iterated funcion systems. This article is concerntrated on the second aspect. And mainly discuss three subjects as following: (a) the partitioning of the image into ranges of the encoding step; (b) the choice of the domain blocks; (c) classifiction methods for the complexity reduction of the encoding step.

Alternate abstract:

随着信息技术特别是多媒体技术应用的日益普及，各种各样的信息（如声音、文字、图象等）在介质中占用越来越大的空间，如何对这些信息进行快速地检索、分类、存储、传送及显示，是当前所面临的最为迫切的问题之一，而解决这一问题的关键即是数据压缩技术。 虽然在静止图象压缩技术上已经有JPEG 作为国际标准，人们仍然在控索许多其它新方法。分形压即是其中最具魅力的一种。 自从Bansley 于1978年提出分形压缩概念至今，发展迅速，产生了多种具体方法。主要分为两类：基于基本迭代函数系统的方法和基于局部迭代函数系统的方法。 本文在简要回顾了图象压缩编码的基本原理、人的视觉特性和图象压缩编码的国际标准之后，指出了离散余弦换 （DCT）算法的不足之处，介绍了分形图象压缩的一些基本概念和以分形概念为基础的几种图象压缩编码方法，重点介结了如何利用局部迭代函数系统（LIFS） 进行图象压缩编码，以实现高压缩比图象压缩编码的具体算法。