【作者】 王宁宁；

【导师】 王以治；

【作者基本信息】 华中科技大学 ， 计算数学， 2004， 硕士

【摘要】 小波分析和小波变换是八十年代后期发展起来的一种信号处理手段,由于其在时间(空间)频率域良好的局部化性能,特别有利于非平稳信号分析,近年来在信号处理的各个领域得到了广泛的应用。本文主要研究将零树编码应用于静止图像压缩编码。尽管小波变换对图像处理非常有效,但不同的小波基对图像编码的效果是不同的。我们研究了几种常用的正交小波基和双正交小波基,实验表明在图像处理中,具有线性相位,正则性的,完全重构的双正交小波基比正交小波基更利于图像压缩。零树编码在图像压缩中有重要地位,本文重点讨论了零树编码在无失真图像压缩中的应用,本文理论上讨论了影响零树编码效率,并给出了影响编码效率的3个主要参数,即小波基的选取、剩余矩阵编码、零树编码层数。小波分解形成了图像能量的聚集,这种聚集可以形成更多的零树,而MSR作为对对偶小波波形集中度的度量参数,同样也可以作为衡量零树编码效率的度量。对于零树编码的层数通过最少零树编码所需要的比特数来确定。对于剩余矩阵R的编码,通过统计的方法,采用了算术编码。更多还原

【Abstract】 The wavelet analysis and the wavelet transform are new tools of signal processing developed in later period of 80’s. Because of their good local performances in both time (space) and frequency, they are particular for the analysis of non-stationary signals and have been used in various fields of signal processing recently. In this dissertation, the still image compression based on wavelet transform is studied.Although wavelet transform is efficient for image processing, different wavelet bases have different efficiency for image coding. Our research shows that linear phase, prefect reconstruction and regularity biorthogonal wavelet filter banks are better than orthonormal wavelet filter banks for image compression.Zero-trees coding is one of the most efficient still image compression , this paper focused on the discussion about zero-trees in the lossless image compression, and analysis the three parameters—the choose of wavelet based, the rest matrix coding and the layer of zero-trees—which effected the efficiency of zero-trees coding and gave the means of how to choose the parameters. Wavelet decompose can made the energy of image get together to the low frequency, thus it can form more zero-trees and MSR as the measure of the efficiency of Zero-trees coding. The layer of the Zero-trees coding can be got by the minimum bits of Zero-trees coding. The rest matrixes R coding adopts the math coding though statistics methods.更多还原