Image restoration with impulse noise based on fractional-order total variation and framelet transform

Restoring images corrupted by noise and blur is a burgeoning subject in image processing, and despite the large number of proposed restoration algorithms, the effort to bring about some improvement is always of great interest. The definition of fractional derivatives in recent years has created a po...

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Bibliographic Details
Published inSignal, image and video processing Vol. 17; no. 5; pp. 2455 - 2463
Main Author Parvaz, Reza
Format Journal Article
LanguageEnglish
Published London Springer London 01.07.2023
Springer Nature B.V
Subjects
Algorithms
Computer Imaging
Computer Science
Image processing
Image Processing and Computer Vision
Image restoration
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Signal,Image and Speech Processing
Vision
Fractional total variation
Framelet
Image deblurring
Nonconvex
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Summary:Restoring images corrupted by noise and blur is a burgeoning subject in image processing, and despite the large number of proposed restoration algorithms, the effort to bring about some improvement is always of great interest. The definition of fractional derivatives in recent years has created a powerful tool for this purpose. In the present paper, using fractional-order total variation and framelet transform, the nonconvex model for image restoration with impulse noise problem is improved. Then by alternating direction method of multipliers (ADMM) and primal-dual problem, the proposed model is solved. The convergence of the proposed algorithm is studied, and the proposed algorithm is evaluated using different types of tests.
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ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-022-02462-2