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19 August 2010A new algorithm for image denoising based on tetrolet transform
This paper introduces a new class of denoising function that has continuous derivative for image denoising. And a
new algorithm are presented. First, we apply tetrolet transform to noise image and obtained tetrolet coefficient. Second,
by using the new denoising function, we present an adaptive method based on SURE Risk. Instead of the global
hard-thresholding algorithm for image denoising, we minimize an estimate of the mean square error by using adaptive
genetic algorithm. At last Numerical experiments show that the proposed new algorithm can significantly outperform
the original hard-thresholding method both in terms of PSNR and in visual quality.
Cai-lian Li,Ji-xiang Sun, andYao-hong Kang
"A new algorithm for image denoising based on tetrolet transform", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201L (19 August 2010); https://doi.org/10.1117/12.866702
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Cai-lian Li, Ji-xiang Sun, Yao-hong Kang, "A new algorithm for image denoising based on tetrolet transform," Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201L (19 August 2010); https://doi.org/10.1117/12.866702