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Proceedings Paper

Region-based image denoising through wavelet and fast discrete curvelet transform
Author(s): Yanfeng Gu; Yan Guo; Xing Liu; Ye Zhang
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Paper Abstract

Image denoising always is one of important research topics in the image processing field. In this paper, fast discrete curvelet transform (FDCT) and undecimated wavelet transform (UDWT) are proposed for image denoising. A noisy image is first denoised by FDCT and UDWT separately. The whole image space is then divided into edge region and non-edge regions. After that, wavelet transform is performed on the images denoised by FDCT and UDWT respectively. Finally, the resultant image is fused through using both of edge region wavelet cofficients of the image denoised by FDCT and non-edge region wavelet cofficients of the image denoised by UDWT. The proposed method is validated through numerical experiments conducted on standard test images. The experimental results show that the proposed algorithm outperforms wavelet-based and curvelet-based image denoising methods and preserve linear features well.

Paper Details

Date Published: 12 January 2009
PDF: 6 pages
Proc. SPIE 7133, Fifth International Symposium on Instrumentation Science and Technology, 713327 (12 January 2009); doi: 10.1117/12.814039
Show Author Affiliations
Yanfeng Gu, Harbin Institute of Technology (China)
Yan Guo, Harbin Institute of Technology (China)
Xing Liu, Harbin Institute of Technology (China)
Ye Zhang, Harbin Institute of Technology (China)


Published in SPIE Proceedings Vol. 7133:
Fifth International Symposium on Instrumentation Science and Technology
Jiubin Tan; Xianfang Wen, Editor(s)

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