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A gradient‐type iterative method for impulse noise removal
Author(s) -
Liu Jinkui,
Cao Haisong,
Zhao Yongxiang,
Zhang Liqiao
Publication year - 2021
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.2358
Subject(s) - mathematics , line search , impulse noise , noise reduction , conjugate gradient method , gradient descent , algorithm , impulse (physics) , mathematical optimization , image restoration , minification , iterative method , inverse problem , noise (video) , image (mathematics) , computer science , image processing , mathematical analysis , artificial intelligence , artificial neural network , pixel , physics , computer security , quantum mechanics , radius
Image denoising is a typical inverse problem and is hard to be solved. Fortunately, a powerful two‐phase method for restoring images corrupted by high‐level impulse noise has been proposed. The key point of the method is the computational efficiency of the second phase which requires the minimization of a smooth objective function defined on the terms of edge‐preserving potential function. In this paper, we propose an effective three‐term conjugate gradient method to restore the corrupted images in the second phase of two‐phase method. An attractive feature of the proposed method is that the search direction satisfies the sufficient descent property at each iteration without any line search. The global convergence is established for general smooth functions under the Armijo‐type line search. Preliminary numerical results are reported to indicate that the proposed method to be used for impulse noise removal is promising.