The denoising results yielded by different algorithms on a dataset with Gaussian noise at a level of <i>σ</i> = 10<sup>−2</sup> after 30 iterations.

The denoising results yielded by different algorithms on a dataset with Gaussian noise at a level of <i>σ</i> = 10<sup>−2</sup> after 30 iterations.

<p>(a) denotes the original image, and (b)–(g) denote the denoised images produced by the ISTA, WLQ, IRW, IRL1, TwIST and the ERIWSTA, respectively.</p>

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Bibliographic Details
Main Author:	Limin Ma (556873) (author)
Other Authors:	Bingxue Wu (13131591) (author), Yudong Yao (10133783) (author), Yueyang Teng (3152376) (author)
Published:	2024
Subjects:	Biotechnology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified lagrange multiplier method problems may make inaccurate solution results iterative weighted shrinkage imaging </ p entropy regularization term classic optimization algorithm making different features iterative shrinkage processes features inverse problems experimental results different attributes xlink "> usual definition thresholding algorithm solving ill paper proposes objective function interpretation ability improved versions existing methods evident advantage convergence speed computed tomography
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