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静止图象的小波压缩研究
Alternative TitleOn Wavelet Compression of Still Images
夏勇
Subtype工学硕士
Thesis Advisor戴汝为
1998-03-01
Degree Grantor中国科学院自动化研究所
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword多媒体通信 图象压缩 图象编码 小波变换 多分辨分析 量化 滤波器设计 零树 Multimedia Communication Image Compression Image Coding Wavelet Transform Multiresolution Analysis Quantization Filter Design Ze
Abstract图象压缩在实际的多媒体通信系统中处于至关重要的位置。我们首先认识图 象压缩技术在数字通信系统模型中的具体作用,并从信息论的角度探讨其基本的 出发点。然后,我们定义了衡量压缩算法性能的几个参数,按照不同的标准对压 缩技术进行了分类,简略地介绍了国际标准压缩算法。 在第二章中,我们介绍了本文工作的数学理论基础——小波分析,包括 Fourier变换,Gabor变换,短时Fourier变换,连续小波变换,框架,小波级 数,多分辨分析,以及二进小波变换的快速Mallat算法等。 接着,我们给出了一般的基于变换的图象压缩算法的框架。为了将小波理论 应用于图象的分解与合成,我们分析了二维可分离的与非分离的小波变换方式, 并详细地讨论了正交与双正交小波,小波基的选取,图象边界延拓等问题。我们 对八十年代以来主要的小波压缩方法作了比较全面的综述。 在第四章中,我们首先仔细地分析了图象经过小波分解以后的空间一频率特 性,特别指出了小波滤波器同时具有频率域和空间域的局部化能力,以及小波系 数分布的级问自相似性。以此为出发点,我们深入地分析了几个性能优异的有代 表性的零树压缩算法,并讨论了这一类算法与空间域的压缩算法相结合的可能 性,在此基础上,通过抑制高频噪声和统计优化系数重建值改进了上述算法。我 们将零树算法应用于指纹图象压缩,取得了很好的结果。 最后,我们展望了未来静止与运动图象压缩研究可能的发展方向。
Other AbstractThis thesis dedicates itself to the research on still image compression. Image compression is crucial in practical multimedia communication system. At first, the role of image compression in the model of digital communication system is discussed. Information theory is selected as the root for image compression research. Then, several parameters are defined to judge the compression performance. The compression techniques are classified and several international image compression standards are briefly introduced. In chapter 2 we give a brief description of the mathematical theory wavelet analysis on which the paper based, including Fourier transform, Gabor transform, short time Fourier transform, continuos wavelet transform, frame, wavelet progression, multiresolution analysis, fast Mallat algorithm of dyadic wavelet transform, etc. A general transform-based image compression framework is given in chapter 3. To practically apply wavelet theory to decomposition and reconstruction of images, we introduce both 2-dimensional separable and non-separable wavelets. Problems such as orthogonal and biorthogonal wavelets, selection of wavelet bases, image margin extension are all discussed. At the end of the chapter we summarize the wavelet image compression methods since 1980's. We in chapter 4 detailly analyze the spatial-frequencial characteristics of wavelet transformed images. The spatial and frequencial localization capability of wavelet filters and self-similarity of wavelet coefficients across decomposition levels are especially pointed out. Based on above discussion, we thoroughly analyze two excellent zero-tree compression algorithms. The possibility for the integration of these frequencial compression algorithms and spatial compression methods is also explored. Through suppressing high frequency noises and statistically optimizing coefficient reconstruction values the above algorithms are improved. The zero-tree algorithm is used to code and decode grayscale fingerprint images. Excellent results are achieved. Finally, we give a conjecture of the future research directions for still and dynanfic image compression.
shelfnumXWLW460
Other Identifier460
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7211
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
夏勇. 静止图象的小波压缩研究[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,1998.
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