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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*
引用本文: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.
作者姓名:王相海  孙 丽  万宇  王爽  陶兢喆
作者单位:1.辽宁师范大学 计算机与信息技术学院 大连 116029
2. 辽宁师范大学 数学学院 大连 116029
3. 辽宁师范大学 城市与环境学院 大连 116029
基金项目:国家自然科学基金项目(No.61402214,41271422)、高等学校博士学科点专项科研基金项目(No.20132136110002)、辽宁省博士科研启动基金项目(No.20121076)、辽宁省教育厅科学研究一般项目(No.L2014423)资助
摘    要:遥感图像修复技术对于后续遥感图像的处理与应用具有重要意义.文中在深入研究曲率驱动(CDD)模型和样本填充算法的基础上,针对遥感图像对纹理细节和边缘区域要求较高的特点,提出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.该算法较好地避免CDD模型修复过程中在一些极端情况下可能出现的假边缘、阶梯效应和扩散速度缓慢等缺点,保证遥感图像修复后的纹理细节信息和边缘信息.仿真实验验证文中算法的有效性.

关 键 词:遥感图像修复    非局部均值    曲率驱动(CDD)模型    梯度引导函数  
收稿时间:2016-01-14

Remote Sensing Image Inpainting Based on Non-local Sample Filling and Adaptive Curvature Driven Diffusions Model
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[J].Pattern Recognition and Artificial Intelligence,2016,29(8):735-743.
Authors:WANG Xianghai  SUN Li  WAN Yu  WANG Shuang  TAO Jingzhe
Affiliation: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.
Keywords:Remote Sensing Image Inpainting  Non-local Means  Curvature Driven Diffusions (CDD) Model  Guide-Function of Gradient  
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