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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.
Yanfeng Gu,Yan Guo,Xing Liu, andYe Zhang
"Region-based image denoising through wavelet and fast discrete curvelet transform", Proc. SPIE 7133, Fifth International Symposium on Instrumentation Science and Technology, 713327 (12 January 2009); https://doi.org/10.1117/12.814039
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Yanfeng Gu, Yan Guo, Xing Liu, Ye Zhang, "Region-based image denoising through wavelet and fast discrete curvelet transform," Proc. SPIE 7133, Fifth International Symposium on Instrumentation Science and Technology, 713327 (12 January 2009); https://doi.org/10.1117/12.814039