Image Denoising with Contour-Based Directionlet Transform

A novel mutiscale and directionally adaptive image transform called contour based directionlet tansform is presented. Directionlet transform (DT) has shown its charming performance in image processing, but it has scrambled frequencies. Laplacian Pyramid is employed here to separate the low frequenci...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 513-517; no. Applied Science, Materials Science and Information Technologies in Industry; pp. 3607 - 3611
Main Authors Xu, Huan An, Liu, Zhe, Peng, Guo Hua
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 06.02.2014
Subjects
Adaptive algorithms
Low frequencies
Mathematical models
Noise reduction
Pyramids
Shape
Transforms
Contour Based Directionlet Transform
Image De-Noising
Directionlet Transform
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Summary:A novel mutiscale and directionally adaptive image transform called contour based directionlet tansform is presented. Directionlet transform (DT) has shown its charming performance in image processing, but it has scrambled frequencies. Laplacian Pyramid is employed here to separate the low frequencies before applying DT for avoiding the drawback. And an adaptive threshold algorithm is proposed for denoising. Numerical experiments are performed to assess the applicability of the proposed method. The obtained results show that the proposed scheme outperforms Wavelet and Directionlet transforms in terms of numerical and perceptual quality.
Bibliography:Selected, peer reviewed papers from the 2014 International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI 2014), January 11-12, 2014, Xi’an, China
ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISBN:9783038350125
3038350125
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.513-517.3607