Image Compression and Indexing Methods Based on Iterative Function System
基于迭代分形的图象压缩和检索方法

Due to the enormous magnitude and unstructured contents of multimedia data, solutions must be provided for their effective compression and efficient indexing, in order to realize all kinds of multimedia applications. However, the traditional approaches treat compression and indexing problems separately during the past decades. The compression algorithms are implemented without indexing supported in compressed domain while the indexing operations are mainly undertaken in original format of multimedia data, resulting in lower overall performance of current multimedia application system. In order to improve the situation, a joint image compression indexing algorithm based on iterative fractal method is proposed in this paper. Firstly, the iterative fractal method is employed to compress the image in wavelet domain for effective compression. Then feature vectors representing the distribution properties of IFS(Iterative Function System) are constructed to support the indexing of images based on the fractal coded image data. Simulation results verify the efficiency of the methods and show the potentials of the fractal based image indexing methods.