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IJEETC 2024 Vol.13(2): 160-167
doi: 10.18178/ijeetc.13.2.160-167

Restoration of Radiographic Neutron Image Using Single-Channel Blind Deconvolution

Y. Khairiah1,2,*, A. Mohd Zaid1, and I. Haidi1
1. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia
2. Reactor Technology Center, Malaysian Nuclear Agency, Bangi, Malaysia
Email: khairiah@nm.gov.my (Y.K.), mza@usm.my (A.M.Z.), haidi@usm.my (I.H.)
*Corresponding author

Manuscript received September 1, 2023; revised November 19, 2023; accepted January 18, 2024.

Abstract—This paper addresses the challenge of accurately estimating the 2D Point Spread Function (PSF) or blur kernel in neutron radiography, where traditional methods, such as the Edge Spread Function (ESF), prove time-consuming and reliant on manual edge selection. The proposed alternative introduces a robust sparse image prior known as the enhanced Patch-Wise Intensity (EPI) image prior in a singlechannel blind deconvolution algorithm, avoiding the need for intricate devices like pinhole or slit phantoms. Leveraging regularization and optimization techniques, the algorithm efficiently estimates PSF in a single image through a multilayer iterative alternating approach. The study aims to enhance PSF accuracy, leading to a more accurate solution to the neutron image restoration problem. Comparative results with real neutron images indicate the proposed method outperforms ESF, demonstrating improved overall image quality both visually and quantitatively in terms of blind/no reference evaluation (BRISQUE).

Index Terms—Point Spread Function (PSF) estimation, blind deconvolution, neutron images and image restoration

Cite: Y. Khairiah, A. Mohd Zaid, and I. Haidi, "Restoration of Radiographic Neutron Image Using Single-Channel Blind Deconvolution," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 13, No. 2, pp. 160-167, 2024. doi: 10.18178/ijeetc.13.2.160-167

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.