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Content Provider | IEEE Xplore Digital Library |
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Author | Tu Xionggang Chen Jun |
Copyright Year | 2009 |
Abstract | The paper presents a image denoising approach based on Support Vector Machine (SVM) . The method proposed here employs the regression capability offered by SVM network to construct a filter for image denoising, where our feather selection and training data-set design enables the suppression of various kinds of noises. Our experimental results demonstrate that the proposed method works well for image denoising while edge information is substantially retained, thus it can be used as a promising image preprocessing tool. |
Starting Page | 269 |
Ending Page | 272 |
File Size | 485313 |
Page Count | 4 |
File Format | |
ISBN | 9781424464203 |
e-ISBN | 9781424464210 |
DOI | 10.1109/IITAW.2009.125 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2009-11-21 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Support vector machines Image Denoising Machine learning algorithms Wavelet domain Noise reduction Support Vector Machine Application software Kernel Information technology Machine intelligence Image denoising Wavelet coefficients |
Content Type | Text |
Resource Type | Article |
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