Share Email Print
cover

Proceedings Paper

Mixed pulse-Gaussian denoising algorithm for improving image quality in assembly inspection of nuclear power plants
Author(s): Congzheng Wang; Song Hu; ChunMing Gao; Chang Feng
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Visual inspection for nuclear fuel assemblies is necessary during outages of nuclear power plants. These inspections can be used to identify fuel assemblies’ anomalies that endanger the reactor’s running. However, intense radiation of fuel assembly sensitively degrades the image quality through a mixture of impulse and Gaussian noise. To solve this problem, an image denoising algorithm based on Non-Local Dual Denoising (NLDD) and Rank-Ordered Absolute Differences (ROAD) is proposed here. It consists of two steps. The detector ROAD is first used to find noisy pixels in an image damaged by impulse noise and replace them with neighborhood values. Then, NLDD filter is applied to image corrupted with Gaussian noise and retains the details. The proposed approach has been successfully tested on assembly inspection of nuclear power plants. The results reveal that our approach is effective to noise suppression and crucial detail preservation.

Paper Details

Date Published: 24 October 2017
PDF: 5 pages
Proc. SPIE 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications, 104624Y (24 October 2017); doi: 10.1117/12.2285652
Show Author Affiliations
Congzheng Wang, Institute of Optics and Electronics (China)
Univ. of Electronic Science and Technology of China (China)
Univ. of Chinese Academy of Sciences (China)
Song Hu, Institute of Optics and Electronics (China)
ChunMing Gao, Univ. of Electronic Science and Technology of China (China)
Chang Feng, Institute of Optics and Electronics (China)


Published in SPIE Proceedings Vol. 10462:
AOPC 2017: Optical Sensing and Imaging Technology and Applications
Yadong Jiang; Haimei Gong; Weibiao Chen; Jin Li, Editor(s)

© SPIE. Terms of Use
Back to Top