Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Improving laser image resolution for pitting corrosion measurement using Markov random field method
Abstract To characterize the pitting corrosion of metallic pipe, high-resolution laser scan is indispensable. In many cases, only low-resolution scan can be obtained due to the limitations of the scanning equipment or time constraint. Although interpolation method can be applied to enlarge the low-resolution image, the enlarged laser scan loses the details of surface topography, which are important to calculate the parameters of pitting corrosion. In this paper, a singe-frame super resolution method is proposed to infer a high-resolution laser scan from the low-resolution input. The relationship between the low-resolution input and high-resolution result is modeled with a Markov random field (MRF) with the aid of a training set built in advance. A belief propagation algorithm is implemented to infer the super-resolved result. The experiments demonstrate a good performance of the proposed method in comparison with the traditional interpolation methods.
Research highlights ►A single-frame super resolution is proposed to improve laser scan for pitting corrosion measurement. ► Markov random field (MRF) is adopted to model the relation between the low resolution scan and the high-resolution result. ► The proposed method can achieve the same quality as high resolution scan while saving the pipe scanning time.
Improving laser image resolution for pitting corrosion measurement using Markov random field method
Abstract To characterize the pitting corrosion of metallic pipe, high-resolution laser scan is indispensable. In many cases, only low-resolution scan can be obtained due to the limitations of the scanning equipment or time constraint. Although interpolation method can be applied to enlarge the low-resolution image, the enlarged laser scan loses the details of surface topography, which are important to calculate the parameters of pitting corrosion. In this paper, a singe-frame super resolution method is proposed to infer a high-resolution laser scan from the low-resolution input. The relationship between the low-resolution input and high-resolution result is modeled with a Markov random field (MRF) with the aid of a training set built in advance. A belief propagation algorithm is implemented to infer the super-resolved result. The experiments demonstrate a good performance of the proposed method in comparison with the traditional interpolation methods.
Research highlights ►A single-frame super resolution is proposed to improve laser scan for pitting corrosion measurement. ► Markov random field (MRF) is adopted to model the relation between the low resolution scan and the high-resolution result. ► The proposed method can achieve the same quality as high resolution scan while saving the pipe scanning time.
Improving laser image resolution for pitting corrosion measurement using Markov random field method
Wu, Wei (Autor:in) / Liu, Zheng (Autor:in) / Krys, Dennis (Autor:in)
Automation in Construction ; 21 ; 172-183
04.06.2011
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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