Paper
7 November 2018 A turbulence image restoration algorithm for subpixel position of location holes on nuclear fuel assemblies
Author Affiliations +
Abstract
In nuclear power plants, it is a common procedure to use video inspection when reloading fuel assemblies regularly. Because of the turbulence generated by residual heat of nuclear fuel assemblies, a video sequence suffers from severe geometric deformations and is hard to be used to position the location hole of fuel assemblies. The paper proposes a novel algorithm to recover a geometrically correct image of nuclear fuel assemblies or scene from a video sequence distorted by turbulence underwater and achieve the precise position of the location hole. At the first, an average image is utilized to compare with image sequences to estimate nonrigid registration based on B-splines. By the estimated nonrigid registration, new image sequences are obtained and are used to get a new average image. After multiple iterations, the better image sequence can be shown. Then the better image sequence are divided into image patches. The more blurry and severely distorted image patches are removed in image patch sequences. Finally, the selected image patches are synthesized together. Based on restored images, template matching is utilized to quickly find the initial position of the location hole. And then the sub-pixel centroid method is used to achieve the sub-pixel position in the image. The calibrated camera parameters are utilized to calculate the position of the location hole of the fuel assemblies. Experiments verify that the algorithm can online locate the center of location holes on recovered images underwater, and has high measurement precision.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wenjun Chen, Zheng Zheng, and Zhang Zhen "A turbulence image restoration algorithm for subpixel position of location holes on nuclear fuel assemblies", Proc. SPIE 10819, Optical Metrology and Inspection for Industrial Applications V, 108191K (7 November 2018); https://doi.org/10.1117/12.2500836
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KEYWORDS
Image restoration

Image quality

Video

Turbulence

Image processing

Distortion

Edge detection

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