期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2012
卷号：1
期号：10
页码：121-126
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Image denoising is a method of removal of noise while preserving as much as possible important information. Basically there are two classes of the image denoising, namely spatial filtering methods and transform filtering methods. A wavelet transform domain method gives a superior performance in image denoising applications. But due to attractive merits of the extensions of the DWT, the research was shifted towards the extensions of the DWT. The first three sections of this paper explain about the basic introduction to the subject, about Wavelet Transform and its types, and about present theories of the topic. Remaining sections explain about DWT extensions and methodologies of the DWT extensions. The wavelet based denoising algorithms use DWT (Discrete Wavelet Transform) in the decomposition stage. But they suffer from lack of directionality and shift variance. To overcome this, CWT (Complex Wavelet Transform) can be used in two modes namely, Dual-Tree Complex DWT and Double-Density Complex DWT. In this paper, these two modes are compared.
