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A Multiscale and Multidirectional Image Denoising Algorithm Based on Contourlet Transform
Pasadena, California, USA December 18-December 20
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IIH-MSP.2006.192006 International Conference on Inte ...
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Bei-bei Li, Jilin University, China
Xin Li, Jilin University, China
Shu-xun Wang, Jilin University, China
Hai-feng Li, Jilin University, China
In this paper, we propose a novel image denoising algorithm in Contourlet domain. The Contourlet transform is adopted by virtual of its advantages over the Wavelet transform in order to obtain a flexible multiresolution, local, and directional image expansion using contour segments, it is good at isolating the smoothness along the contours. We present a weighing factor which submits to the negative exponential distribution, it can combine the hard thresholding function with the soft thresholding, the new thresholding function is continuous[4]. We adapt different thresholdings on different scales and different directions to get better denoising results. Experimental results demonstrate that the proposed algorithm improves the SNR on a certain extent.
Citation:
Bei-bei Li, Xin Li, Shu-xun Wang, Hai-feng Li, "A Multiscale and Multidirectional Image Denoising Algorithm Based on Contourlet Transform," iih-msp, pp.635-638, 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP'06), 2006
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