Inpainting method for flash radiographic anti-scatter grid image based on neural networks

Jing Yuefeng; Liu Jun; Guan Yonghong

doi:10.3788/HPLPB20132503.0751

Volume 25 Issue 03

Mar. 2013

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Article Navigation > High Power Laser and Particle Beams > 2013 > 25(03): 751-754

Zheng Zheng, Wu Hongchun, Cao LiangZhi, et al. Application of Monte Carlo and discrete ordinate coupling method to pressurized water reactor cavity radiation streaming calculation[J]. High Power Laser and Particle Beams, 2012, 24: 2946-2950. doi: 10.3788/HPLPB20122412.2946

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Jing Yuefeng, Liu Jun, Guan Yonghong. Inpainting method for flash radiographic anti-scatter grid image based on neural networks[J]. High Power Laser and Particle Beams, 2013, 25: 751-754. doi: 10.3788/HPLPB20132503.0751

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Inpainting method for flash radiographic anti-scatter grid image based on neural networks

doi: 10.3788/HPLPB20132503.0751

1.
Institute of Fluid Physics,CAEP,P.O.Box 919-105,Mianyang 621900,China

Received Date: 2012-05-22
Rev Recd Date: 2012-08-16
Publish Date: 2013-03-05

Abstract

Abstract

To solve the problem of flash radiographic anti-scatter grid image inpainting, a radial basis function (RBF) neural network based image inpainting algorithm is proposed. First the anti-scatter grid image is divided into a series of blocked images. Then the weights of the RBF network are estimated and a continuous function is constructed in each blocked image, and with them the pixels of missing information can be filled in. The experimental results show that the new algorithm has better general performance in inpainting quality and boundary maintenance compared with the linear interpolation and spline interpolation method.
- image inpainting,
- flash X-ray radiography,
- neural network,
- radial basis function

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