Translator Disclaimer
2014 Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation
Hamid A. Jalab
Abstr. Appl. Anal. 2014(SI40): 1-8 (2014). DOI: 10.1155/2014/590947

Abstract

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.

Citation

Download Citation

Hamid A. Jalab. "Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation." Abstr. Appl. Anal. 2014 (SI40) 1 - 8, 2014. https://doi.org/10.1155/2014/590947

Information

Published: 2014
First available in Project Euclid: 6 October 2014

zbMATH: 07022668
Digital Object Identifier: 10.1155/2014/590947

Rights: Copyright © 2014 Hindawi

JOURNAL ARTICLE
8 PAGES


SHARE
Vol.2014 • No. SI40 • 2014
Back to Top