Improving performance of K-SVD based image denoising using curvelet transform

S Routray, AK Ray, C Mishra - 2015 International Conference …, 2015 - ieeexplore.ieee.org
2015 International Conference on Microwave, Optical and …, 2015ieeexplore.ieee.org
Image denoising algorithm in transform domain which uses learning of dictionary has better
PSNR performance than others. It is seen that the popular algorithms based on K-SVD
proposed earlier has still in use. However, the texture part of the image could not be
preserved during the process of denoising. It is also seen that the effect becomes more
visible with increased value of standard deviation of the Gaussian noise. The proposed
algorithm in this work uses curvelet transform along with K-SVD to retain the texture part of …
Image denoising algorithm in transform domain which uses learning of dictionary has better PSNR performance than others. It is seen that the popular algorithms based on K-SVD proposed earlier has still in use. However, the texture part of the image could not be preserved during the process of denoising. It is also seen that the effect becomes more visible with increased value of standard deviation of the Gaussian noise. The proposed algorithm in this work uses curvelet transform along with K-SVD to retain the texture part of the image. The denoising with the proposed method shows better PSNR performance as compared to denoising with only K-SVD.
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