Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-25
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The interest in using fractional mask operators based on fractional calculus operators has grown for image denoising.
Denoising is one of the most fundamental image restoration problems in computer vision and image processing.
This paper proposes an image denoising algorithm based on convex solution of fractional heat equation with regularized fractional power parameters.
The performances of the proposed algorithms were evaluated by computing the PSNR, using different types of images.
Experiments according to visual perception and the peak signal to noise ratio values show that the improvements in the denoising process are competent with the standard Gaussian filter and Wiener filter.
American Psychological Association (APA)
Jalab, Hamid A.. 2014. Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1014282
Modern Language Association (MLA)
Jalab, Hamid A.. Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation. Abstract and Applied Analysis No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1014282
American Medical Association (AMA)
Jalab, Hamid A.. Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1014282
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1014282