Optimized Hybrid Model for Gaussian Noise Reduction images

Lubna Farhi; Agha Yasir; Farhan Ur Rehman; Baqar Ali Zardari; Ramsha Shakeel; Samia Shakeel

doi:10.52584/QRJ.1901.02

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Optimized Hybrid Model for Gaussian Noise Reduction images

Author(s)

Lubna Farhi Department of Electronic Engineering, Sir Syed University of Engineering and Technology,Karachi,Pakistan

Agha Yasir Department of Electronic Engineering, Sir Syed University of Engineering and Technology,Karachi,Pakistan

Farhan Ur Rehman Department of Mechanical Engineering, University of Toronto,Toronto,Canada

Baqar Ali Zardari Department of Computer Science,QUEST, Nawabshah,Pakistan

Ramsha Shakeel Department of Electronic Engineering, Sir Syed University of Engineering and Technology,Karachi,Pakistan

Samia Shakeel Department of Electronic Engineering, Sir Syed University of Engineering and Technology,Karachi,Pakistan

Abstract

In this paper, image noise is removed by using a hybrid model of wiener and fuzzy filters. It is a challenging task to remove Gaussian noise (GN) from an image and to protect the image’s edges. The Fuzzy-Wiener filter (FWF) hybrid model is used for optimizing the image smoothness and efficiency at a high level of GN. The efficiency is measured by using Structural Similarity (SSIM), Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR). The proposed algorithm substitutes a mean value of the matrix for a non-overlapping block and replaces the total pixel number with each direction. In the proposed model, overall results proved that the optimized hybrid model FWF has an enormous computational speed and impulsive noise reduction, which enables efficient filtering as compared to the existing techniques

Publication Details

Page(s) 9-77

DOI 10.52584/QRJ.1901.02

Published Journal: Quaid-e-Awam University Research Journal of Engineering, Science and Technology, Volume: 19, Issue: 1, Year: 2021

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Keywords

Fuzzy filter, Filtering techniques, Noise removal, Gaussian noise, Weiner filter

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