A Comprehensive Comparative Analysis of Image Restoration Algorithms: Performance Metrics and Insights


  • Engr. Dr. Umer Ijaz Government College University, Faisalabad.
  • Engr. Abubaker Ijaz WASA, Faisalabad
  • Engr. ALI IQBAL Government College University, Faisalabad.
  • Dr. Fouzia Gillani Government College University, Faisalabad.
  • Engr. Muzammil Hayat Government College University, Faisalabad


This research paper presents a rigorous comparative analysis of five leading image restoration algorithms: Wiener Filter, Adaptive Histogram Equalization (AHE), Denoising through Non-Local Means (NLM), Iterative Back Projection (IBP), and Richardson-Lucy (RL) Deconvolution. With a focus on applications in medical imaging, surveillance, and remote sensing, the study addresses challenges related to noise and degradation. Our evaluation, conducted on a diverse dataset, employs key performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Universal Image Quality Index (UIQI). The research yields compelling evidence, positioning the Richardson-Lucy Deconvolution algorithm as the optimal choice. Demonstrating superior performance in high-quality image reconstruction, noise reduction, and structural preservation, RL Deconvolution emerges as the most suitable technique for a range of real-world scenarios. This research contributes pivotal insights, steering the practical application of image restoration towards heightened efficacy and reliability.

Author Biographies

Engr. Dr. Umer Ijaz, Government College University, Faisalabad.

Assistant Professor, Department of Electrical Engineering & Technology

Engr. Abubaker Ijaz, WASA, Faisalabad

Director Development

Engr. ALI IQBAL, Government College University, Faisalabad.

Lecturer, Department of Electrical Engineering and Technology

Dr. Fouzia Gillani, Government College University, Faisalabad.

Department of Mechanical Engineering and Technology

Engr. Muzammil Hayat, Government College University, Faisalabad

Department of Electrical Engineering and Technology

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Electrical Engineering