Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15666
Title: Denoising of Digital Images Using Spatial Domain Edge Detection Approach
Authors: Neole, Bhumika
Pinjarkar, Latika
Patni, Jagdish Chandra
Vidyabhanu, Anusha
Malpani, Anshu
Dudhe, Ojas
Keywords: Bivariate Wavelet Shrinkage
Discrete Wavelet Transform
Psnr
Spatial Domain
Ssim
Issue Date: 2024
Publisher: International Journal of Religion
Transnational Press London Ltd
Citation: Vol. 5, No. 6; pp. 298-307
Abstract: Better results can be produced by the Hybridization of the Wavelet-based image denoising technique and sparse representation of edges. A novel method for spatial domain edge identification that produces a denoised image that has been tainted by additive white Gaussian noise without sacrificing the image's detail information. By combining bivariate shrinkage and local profile edge detection, a denoised image is produced. In this paper, the hybridization method is proposed by modifying the existing Wavelet Transform for image denoising leading to an increase in the PSNR and SSIM as compared to that given by existing Wavelet denoising techniques, maintaining the visual quality of an image. To modify the wavelet coefficients Bivariate Wavelet Shrinkage is used. The quality assessment is evaluated in terms of SSIM value and PSNR value. © 2024, Transnational Press London Ltd. All rights reserved.
URI: http://dx.doi.org/10.61707/y562qn51
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/15666
ISSN: 2633-352X
Appears in Collections:Journal Articles

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