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Image deblurring using adaptive fractional‐order shock filter
Author(s) -
Irandoustpakchin Safar,
Babapour Shahab,
Lakestani Mehrdad
Publication year - 2021
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.7076
Subject(s) - deblurring , mathematics , filter (signal processing) , image (mathematics) , shock (circulatory) , stability (learning theory) , algorithm , fractional calculus , image restoration , artificial intelligence , computer vision , image processing , computer science , medicine , machine learning
In this paper, a novel image enhancement model based on shock filter for image deblurring is proposed in three cases. For the weight of shock filter, the fractional‐order derivative of initial blurry image is used. This fractional‐order weight can be adjusted adaptively according to the gradient of blurred image. Compared with the traditional integer‐order shock filter, the proposed model creates less staircase effect, whereas the enhancement and deblurring of the resulted images are efficiently good. Stability properties of the proposed method are studied theoretically, and also to show the validity of stability studies results, some numerical experiments are presented. The three cases of proposed method are compared with together and with other methods. Different test images are used to show the validity of these cases. Numerical experiments confirm the efficiency of these cases.