Denoising of Digital Images Using Spatial Domain Edge Detection Approach

Bhumika Neole; Latika Pinjarkar; Jagdish Chandra Patni; Anusha Vidyabhanu; Anshu Malpani; Ojas Dudhe

doi:10.61707/y562qn51

Authors

Bhumika Neole Department of Electronics and Communication, Shri Ramdeobaba College of Engineering and management, Nagpur, India
Latika Pinjarkar Department of Computer Science, Symbiosis Institute of Technology, Nagpur, India
Jagdish Chandra Patni Dept. of CSE, Alliance School of Advanced Computing, Alliance University Bengaluru, India
Anusha Vidyabhanu Department of Electronics and Communication, Shri Ramdeobaba College of Engineering and management, Nagpur, India
Anshu Malpani Department of Electronics and Communication, Shri Ramdeobaba College of Engineering and management, Nagpur, India
Ojas Dudhe Department of Electronics and Communication, Shri Ramdeobaba College of Engineering and management, Nagpur, India

DOI:

https://doi.org/10.61707/y562qn51

Keywords:

Spatial Domain, Bivariate Wavelet Shrinkage, PSNR, SSIM, Discrete Wavelet Transform

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.