Remote Sensing Image Inpainting Based on Non-local Sample Filling and Adaptive Curvature Driven Diffusions Model
WANG Xianghai1,2, SUN Li1, WAN Yu2, WANG Shuang1, TAO Jingzhe3
1.School of Computer and Information Technology, Liaoning Normal University, Dalian 116029 2.School of Mathematics, Liaoning Normal University, Dalian 116029 3.College of Urban and Environmental Science, Liaoning Normal University, Dalian 116029
Abstract：Remote sensing image inpainting technology is significant for the following treatment and application of remote sensing image. Based on a thorough study of curvature driven diffusions (CDD) model and sample filling algorithm, a remote sensing image inpainting algorithm based on non-local sample filling and adaptive curvature driven diffusion model is proposed. The proposed algorithm can avoid the false edge, the staircase effect, the slow diffusion velocity, etc. in some extreme cases during the process of image inpainting. Meanwhile, it maintains the texture feature and edge information well for the inpainted image. The proposed algorithm is verified by simulation experiments.
王相海，孙 丽，万宇，王爽，陶兢喆. 非局域样本填充和自适应曲率驱动模型的遥感图像修复算法*[J]. 模式识别与人工智能, 2016, 29(8): 735-743.
WANG Xianghai, SUN Li, WAN Yu, WANG Shuang, TAO Jingzhe. Remote Sensing Image Inpainting Based on Non-local Sample Filling and Adaptive Curvature Driven Diffusions Model. , 2016, 29(8): 735-743.
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2016, Vol. 29 
