The Optimized Hybrid Model for Gaussian Noise Reduction images

  • Lubna Farhi Sir Syed Univ. of Engineering and Technology
  • Agha Yasir Ali Department of Electronic Engineering, Sir Syed University of Engineering and Technology, Karachi
  • Syed Muslim Jamel Department of Computer Engineering, Sir Syed University of Engineering and Technology, Karachi
  • Farhan ur Rehman Department of Mechanical Engineering, University of Toronto, and Toronto, Canada
  • Baqar Ali Zardari Department of Information Technology, QUEST, Nawabshah, Pakistan.
  • Ramsha Shakeel Department of Electronic Engineering, Sir Syed University of Engineering and Technology, Karachi
  • Samia Shakeel Department of Electronic Engineering, Sir Syed University of Engineering and Technology, Karachi
Keywords: Gaussian Noise, Weiner Filter, Fuzzy Filter, Noise Removal, Filtering Techniques

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.

Published
2021-06-30
How to Cite
Farhi, L., Ali, A., Jamel, S. M., ur Rehman, F., Zardari, B. A., Shakeel, R., & Shakeel, S. (2021). The Optimized Hybrid Model for Gaussian Noise Reduction images. Quaid-E-Awam University Research Journal of Engineering, Science & Technology, Nawabshah., 19(1), 9-17. https://doi.org/10.52584/QRJ.1901.02