结合邻域信息和结构特征的遥感影像变化检测

doi:10.11947/j.AGCS.2021.20200130

摘要/Abstract

摘要： 为提高像元级变化检测方法的精度，提出一种结合邻域信息和结构特征的遥感影像变化检测方法。该方法涵盖邻域相关影像（neighborhood correlation image，NCI）、匹配误差和结构特征3种属性特征。首先，通过邻域相关分析技术获得表示上下文信息的邻域相关影像，利用邻域间像素的互相关性进行模板匹配获得匹配误差。然后，基于方向梯度信息提取能抵抗影像间光谱差异的结构特征。随后将邻域相关影像、匹配误差、结构特征作为决策树的分类属性，获取初始变化检测结果。最后，利用马尔可夫随机场（Markov random field，MRF）对其进行优化，获得最终的二值变化图。本文通过采用两组不同传感器的双时相遥感影像进行试验。结果表明，相较于采用变化向量分析法（change vector analysis，CVA）、单一邻域信息法及邻域信息和纹理特征相结合的方法，本文方法有效提高了变化检测的精度。

关键词: 邻域信息, 匹配误差, 结构特征, 变化检测

Abstract: In order to improve the accuracy of pixel-level change detection methods, this paper proposes a novel change detection method for remote sensing images by combining neighborhood information (including the neighborhood correlation image (NCI) and matching errors) and structural features. First, a technique of neighborhood correlation analysis is used to obtain the NCI which represents the context information, and the cross-correlation of neighborhood pixels is used to obtain matching errors by a template matching scheme. Then, structure features of images are extracted using orientated gradient information, which are robust to spectral differences between images. Subsequently, the initial change detection results is obtained by using the NCI, the matching errors, and structural features as the classification attributes of a decision tree. Finally, the Markov Random Field (MRF) is used to optimize the results, yielding the final binary map. The proposed method has been evaluated with two sets of bi-temporal remote sensing images from different sensors. Experimental results demonstrate that this method effectively improves the accuracy of change detection compared with the change vector analysis method, the single neighborhood information method and the method combining neighborhood information and texture features.

Key words: neighborhood information, matching errors, structural features, change detection

中图分类号:

P237

叶沅鑫, 孙苗苗, 王蒙蒙, 谭鑫. 结合邻域信息和结构特征的遥感影像变化检测[J]. 测绘学报, 2021, 50(10): 1349-1357.

YE Yuanxin, SUN Miaomiao, WANG Mengmeng, TAN Xin. Change detection of remote sensing images by combining neighborhood information and structural features[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(10): 1349-1357.

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