doi: 10.4304/jsw.6.6.1117-1124
Image Denoising Algorithm Based on Dyadic Contourlet Transform
- 1 Shandong Institute of Business and Technology, Yantai, China
- 2 Shandong Normal University, Jinan, China
Abstract
This paper constructs a dyadic non-subsampled Contourlet transform for denoising on the image. The transformation has more directional subband, using the non-subsampled filter group for decompositing of direction, so it has the translation invariance, eliminated image distortion from Contourlet transform’s lack of translation invariance. Non-subsampled filter reduces noise interference and data redundancy. Using the feature of NSCT translation invariance, multiresolution, multidirection, and can according to the energy of NSCT in all directions and in all scale, adaptive denoising threshold. Experimental results show that compared to wavelet denoising and traditional Contourlet denoising, the method achieves a higher PSNR value, while preserving image edge details, can effectively reduce the Gibbs distortion, improve visual images.
Keywords
- component
- Image denoising
- Dyadic conto
How to Cite
Hui Fan, Yongliang Wang, and Jinjiang Li, "Image Denoising Algorithm Based on Dyadic Contourlet Transform," Journal of Software, vol. 6, no. 6, pp. 1117-1124, 2011. https://doi.org/ 10.4304/jsw.6.6.1117-1124
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).