基于小波与分形相结合的图像压缩编码  

Image Compression Encoding Based on Wavelet Transform and Fractal

作　　者：张晶晶 张爱华[1] 纪海峰[1] ZHANG Jing-jing;ZHANG Ai-hua;JI Hai-feng(School of Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)

机构地区：[1]南京邮电大学理学院

出　　处：《计算机科学》2019年第8期310-314,共5页Computer Science

基　　金：江苏省自然科学基金(BK20160800);国家自然科学基金面上项目(11471114,61372125)资助

摘　　要：分形图像编码在较高的压缩比下,可以保持较好的重构图质量;但也存在计算复杂度高和编解码时间长的缺点。因此,在定义一种新的子块特征——框点和的基础上,结合连续小波变换的平滑特性,提出了基于小波与分形相结合的图像压缩编码。该算法充分利用子带的相关性来提高重构图像的质量,将全局搜索转换为近邻搜索,缩小了搜索范围,从而减少了编解码时间。仿真实验结果表明,与基本分形算法和其他算法相比,新算法的性能更优,不仅缩短了编解码时间,而且提高了重构图像的质量。Fractal image encoding with the high compression ratio can maintain a good quality of reconstructed image.However,there are some disadvantages such as high computational complexity and long encoding time.Therefore,based on the definition of a new sub-block feature called sum of frame and point,combined with the smoothing characteristics of continuous wavelet transform,an image compression encoding on the basis of wavelet transform and fractal was proposed.This algorithm makes full use of the correlation of sub-bands,so as to improve the quality of reconstructed ima-ge.And it converts the global search into the nearest neighbor search to shorten search range and reduce encoding and decoding time.The simulation results show that compared with the basic fractal algorithm and other algorithms,the new algorithm has better performance.In addition,it not only shortens the encoding and decoding time,but also improves the reconstructed image quality.

关 键 词：小波 分形 分形图像编码 图像压缩 子块特征 

分 类 号：TN919.81[电子电信—通信与信息系统]