4 March 2015 Image denoising using ridgelet shrinkage
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Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94430X (2015) https://doi.org/10.1117/12.2178701
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
Abstract
Protecting fine details and edges while denoising digital images is a challenging area of research due to changing characteristics of both, noise and signal. Denoising is used to remove noise from corrupted images but in the process fine details like weak edges and textures are hampered. In this paper we propose an algorithm based on Ridgelet transform to denoise images and protect fine details. Here we use cycle spinning on Ridgelet coefficients with soft thresholding and name the algorithm as Ridgelet Shrinkage in order to suppress noise and preserve details. The projections in Ridgelets filter out the noise while protecting the details while the ridgelet shrinkage further suppress noise. The proposed algorithm out performs the Wavelet Shrinkage and Non-local (NL) means denoising algorithms on the basis of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) numerically and visually both.
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Pawan Kumar, Pawan Kumar, Kishore Bhurchandi, Kishore Bhurchandi, } "Image denoising using ridgelet shrinkage", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430X (4 March 2015); doi: 10.1117/12.2178701; https://doi.org/10.1117/12.2178701
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