Characteristics analysis of wavelet coefficients and its applications in image compression

Characteristics analysis of wavelet coefficients and its applications in image compression
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小波系数特性分析及其在图像压缩中的应用

DOI:
10.1142/s0219691314500283
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发表时间:
2014-05
期刊:
International Journal of Wavelets, Multiresolution and Information Processing
影响因子:
--
通讯作者:
Shang, Zhaowei
Shang, Zhaowei
中科院分区:
其他
文献类型:
--
作者:
Tang, Yuan Yan;Yu, Hongnian;Cang, Shuang;Shang, Zhaowei

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目前,小波变换因其优良的去相关性和小波系数所包含的冗余性而被广泛应用于信号处理领域,特别是图像压缩领域。本文研究小波系数任意两个或三个分量、小波基和原始信号之间的冗余关系。我们分别按照连续形式和离散形式讨论了每种情况下的内容,并由此推导出了一个统一的公式,该公式阐明了小波系数的冗余性、小波基和原始信号之间的内在联系。最后,我们介绍了小波系数冗余特性在静止图像压缩领域中的应用,并比较了离散小波变换(DWT)与离散余弦变换(DCT)的特性。
Currently, the wavelet transform is widely used in the signal processing domain, especially in the image compression because of its excellent de-correlation property and the redundancy property included in the wavelet coefficients. This paper investigates the redundancy relationships between any two or three components of the wavelet coefficients, the wavelet bases and the original signal. We discuss those contents for every condition according to the continuous form and the discrete form, respectively, by which we also derive a uniform formula which illuminates the inherent connection among the redundancy of the wavelet coefficients, the wavelet bases and the original signals. Finally, we present the application of the wavelet coefficient redundancy property in the still image compression domain and compare the properties of the Discrete Wavelet Transform (DWT) with that of the Discrete Cosine Transform (DCT).
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