基于自适应非局部模式一致性的多模态遥感影像变化检测方法  

Change detection method based on adaptive nonlocal pattern consistency for multimodal remote sensing images

作　　者：韩特 汤玉奇 陈玉增 张芳艳 杨欣 邹滨[1,2] 冯徽徽 HAN Te;TANG Yuqi;CHEN Yuzeng;ZHANG Fangyan;YANG Xin;ZOU Bin;FENG Huihui(School of Geosciences and Info-physics,Central South University,Changsha 410083,China;Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University),Ministry of Education,Changsha 410083,China;School of Advanced Interdisciplinary Studies,Ningxia University,Zhongwei 755000,China)

机构地区：[1]中南大学地球科学与信息物理学院,长沙410083 [2]中南大学有色金属成矿预测与地质环境监测教育部重点实验室,长沙410083 [3]宁夏大学前沿交叉学院,中卫755000

出　　处：《遥感学报》2024年第12期3197-3212,共16页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:41971313,42271411);湖南省研究生科研创新项目(编号:CX20220169)。

摘　　要：亚热带地区环境复杂,自然灾害频发。多模态遥感影像变化检测可在监测其环境变化与灾害现象中发挥重要作用,已成为当下遥感影像处理的研究热点。针对现有方法存在的目标空间结构特征和影像变化信息利用不足的问题,本文假设地物变化将导致对应影像区域的空间结构特征变化,提出了一种基于自适应非局部模式一致性ANLPC(Adaptive Non-local Pattern Consistency)的多模态遥感影像变化检测方法。该方法通过度量多模态影像的空间结构变化提取影像变化信息。首先利用块相似性构建多模态影像的自适应非局部模式,实现空间结构特征表达;然后通过前/后向模式映射度量其与另一时相影像的空间结构差异;最后融合前/后向变化强度图的频率域信息获取鲁棒的变化强度图,并通过阈值分割得到二值变化检测图。本文采用4组多模态遥感影像数据集(两组光学—SAR(Synthetic Aperture Radar)数据集,两组光学—LiDAR数据集)和两组单模态遥感影像数据集(一组光学影像数据集,一组SAR影像数据集)验证了本文方法的有效性。相对于现有方法,本文方法在6组数据集中的卡帕系数KC平均至少提升17.28%。Multimodal remote sensing image change detection is an active research area in the field of remote sensing image processing and plays a crucial role in disaster monitoring,urban planning,natural resource monitoring,and other domains.To address the problem of insufficient utilization of target spatial structure features and image change information in existing methods,this study proposes that the spatial structure features of unchanged regions in multimodal images are consistent,whereas the spatial structure features of changed regions differ.Therefore,change information can be extracted by measuring the difference in the spatial structure of multimodal images.This study proposes a change detection method based on Adaptive Nonlocal Pattern Consistency(ANLPC)for multimodal remote sensing images.In this study,the basic processing unit for the images is made up of patches that overlap with one another.The target patch is defined as the construction pattern’s reference patch,and the other patches are viewed as homogeneous.The nonlocal mode of the image is constructed adaptively via the homogeneous patch automated selection approach and by using the rank coordinate space of the target patch as the search space to consider the spatial information of the image and narrow the search area.Cross mapping of two temporal image patterns(forward and backward mapping)is achieved by adaptive nonlocal pattern mapping to precisely assess the variation between multimodal images.With forward mapping as an example,ANLPC maps the nonlocal pattern of the first temporal image into the second temporal image domain,and the difference information of the pattern in the second temporal image domain represents the change information of the multimodal image.Similarly,backward change information is acquired from backward mapping.The final difference map is produced by combining the forward and backward difference information via curvelet transform,and the binary change detection results are produced using threshold segmentation.Four multimodal

关 键 词：遥感 多模态影像 变化检测 结构特征 自适应非局部模式 模式映射 影像融合 

分 类 号：P237[天文地球—摄影测量与遥感] P2[天文地球—测绘科学与技术]