强激光与粒子束2013，Vol.25Issue(3)：751-754,4.DOI:10.3788/HPLPB20132503.0751
基于神经网络的闪光照相网栅图像修补
Inpainting method for flash radiographic anti-scatter grid image based on neural networks
摘要
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.关键词
图像修补/闪光照相/神经网络/径向基函数Key words
image inpainting/ flash X-ray radiography/ neural network/ radial basis function分类
信息技术与安全科学引用本文复制引用
景越峰,刘军,管永红..基于神经网络的闪光照相网栅图像修补[J].强激光与粒子束,2013,25(3):751-754,4.基金项目
中国工程物理研究院科学技术发展基金项目(2009A0203013,2010B0202021) （2009A0203013,2010B0202021）
