Inpainting method for flash radiographic anti-scatter grid image based on neural networks
景越峰 Jing Yuefeng, Jun Liu, 管永红 Guan Yonghong · High Power Laser and Particle Beams · 2013
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.