Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Image restoration viawiener filtering in the frequency domain
WSEAS Transactions on Signal Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
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In this paper, we present a denoising technique that is capable for preserving the fine details and edges in the restored image more effectively in blind condition. We also introduce a new edge detection method to detect edges effectively in noisy environments. First, the noisy image is denoised by using different weights of Wiener filtering to generate two restored images; one with highly reduced noise, and the other with preserved fine details and edges. The noise and image power spectra required for the frequency domain Wiener filter are estimated with different threshold setting. Then, an edgemap image is generated directly from the noisy image. The two Wiener filtered images are utilized for the smooth and non-smooth regions based on the constructed edgemap to produce the final restored image. Simulation results show that the proposed method outperforms or is comparable to other Wiener filter-based denoising methods and the state-of-the-art denosing methods, especially in higher noise environments.