New model for local fractional integral of Chebyshev polynomials for image denoising

Suzan Jabbar Obaiys, Hamid A. Jalab, Rabha W. Ibrahim

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Abstract

The use of local fractional calculus has increased in different applications of image processing. This study proposes a new algorithm for image denoising to remove Gaussian noise in digital images. The proposed algorithm is based on local fractional integral of Chebyshev polynomials. The proposed structures of the local fractional windows are obtained by four masks created for x and y directions. On four directions, a convolution product of the input image pixels with the local fractional mask window has been performed. The visual perception and peak signal-to-noise ratio (PSNR) with the structural similarity index (SSIM) are used as image quality measurements. The experiments proved that the accomplished filtering results are better than the Gaussian filter.
Original languageEnglish
Pages (from-to)22-28
Number of pages7
JournalResearch Journal of Computer Science and Engineering
Volume1
Issue number1
DOIs
Publication statusPublished - 18 Nov 2019

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