Image denoising using fractional integral

In order to preserve more image details information while image denoising, the fractional integral operator was introduced to signal processing. The method proposed in this work constructed the corresponding mask of image denoising by setting a smaller fractional order, and controlled the effect of...

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Bibliographic Details
Published in2012 IEEE International Conference on Computer Science and Automation Engineering Vol. 2; pp. 107 - 112
Main Authors Huang Guo, Xu Li, Chen Qing-li, Wang Ming-rong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Filtering algorithms
fractional integral
Image denoising
Image edge detection
iteration
signal noise ratio
Signal to noise ratio
Wiener filters
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ISBN1467300888
9781467300889
DOI10.1109/CSAE.2012.6272738

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Summary:In order to preserve more image details information while image denoising, the fractional integral operator was introduced to signal processing. The method proposed in this work constructed the corresponding mask of image denoising by setting a smaller fractional order, and controlled the effect of image denoising by the way of iteration, so it achieved fine-tuning of image denoising. The experimental results show that the image denoising algorithm based on fractional integral proposed in this work compared with the traditional image denoising algorithm not only enhances the signal-to-noise ratio of image but also better retains the edge and texture details of image.
ISBN:1467300888
9781467300889
DOI:10.1109/CSAE.2012.6272738