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赵元昊，孙根云，张爱竹，矫志军，孙超.XXXX.基于典型相关分析的遥感影像非监督超像素级变化检测.遥感学报，XX（XX）： 1-15
ZHAO Yuanhao，SUN Genyun，ZHANG Aizhu，JIAO Zhijun，SUN Chao. XXXX. Unsupervised super pixel level change detection based on canonical correlation analysis. National Remote Sensing Bulletin， XX（XX）：1-15
变化检测是指利用多时相影像检测地表覆盖类型发生变化的区域，目前的检测方法易受噪声以及特殊地物等影响，检测结果斑点现象严重、检测精度低。针对以上问题，本文结合典型相关分析和直方图规定化提出一种非监督的超像素级变化检测方法。首先，对两个时刻的遥感影像进行预处理以及超像素分割；其次，基于超像素尺度和未发生变化的概率计算每个超像素的权重；然后，基于超像素级多元变化检测和直方图规定化获取变化特征；最后，基于权重影像、经典方法与变化特征进行决策融合，得到变化检测结果图。本文在三个高光谱测试数据集和一个多光谱测试数据集上进行实验验证。结果表明，本文方法在四个测试数据集上的OA和Kappa指标均为最优，且OA都达到了90%以上。在四个数据集上，本文方法的OA相比于其他方法中的最高精度提高了4.41%、3.44%、1.74%和0.19%。
Change detection is the process of detecting the changed surface cover using the multi-phase characteristics. The current detection method is easy to be affected by noise and special objects, which makes the detection result of spot phenomenon serious and the detection accuracy low. To solve this problem, this paper proposes an unsupervised super pixel level change detection method based on canonical correlation analysis and histogram specification. Firstly, the remote sensing images at two times are preprocessed and super-pixel segmented; Secondly, the weight of each super-pixel is calculated based on the super-pixel scale and the unchanged probability; Then, the change features are obtained based on super-pixel multivariate change detection and histogram specification; Finally, based on the weighted image, classical methods and change features, the change detection result map is obtained.In this paper, three hyperspectral test data sets and one multispectral test data set are used for experimental verification. The results show that the OA and Kappa indexes of our method on four test datasets are the best, and the OA of four test datasets all above 90%. On the four data sets, the OA of our method is improved by 4.41%, 3.44%, 1.74% and 0.19% compared with other methods.
超像素变化检测典型相关分析直方图规定化
super pixelchange detectioncanonical correlation analysishistogram specification
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