文章基本信息

标题：A Detailed Study on Image Denoising Algorithms by Using the Discrete Wavelet Transformation
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作者：Asem Khmag ; Abd Rahman Ramli ; Syed Abdul Rahman Al-Haddad 等
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2014
卷号：5
期号：1
语种：English
出版社：Ayushmaan Technologies
摘要：The seeking for an efficient image denoising methods is still a valid challenge at the researches field of image analysis and processing. In spite of the sophistication and extreme researches in the recent years, most algorithms have not yet reach a desirable level of applicability. All the algorithms and methods present a high outstanding performance when the image model corresponds to the algorithm assumptions but it fails in general and create artifacts and blurred texture or change the main structures of the original image. De-noising of natural images corrupted by Additive white Gaussian noise using wavelet based technique has its effectively performance because of its ability to capture the energy of the signal in few energy transform values or coefficients. This method performs well under a number of applications because wavelet transform has the compaction property of having only a small number of large coefficients where the remaining wavelet coefficients are very small. The aim of this study is to examine a wide range of existing studies in the literature related to applying wavelet transformation for denoising natural images. Furthermore, this study is done to review various denoising algorithms using wavelet transform; those algorithms are discussed with specific details in order to understand the effect of each algorithm on the quality of the image. Algorithms such as SureShrink, Bivariate Shrink, VisuShrink, BayesShrink, Neigh Shrink and Normal shrink are presented in this paper. A different Gaussian white noise levels in PSNR are shown in the experimental results.