论文标题
基于自适应局部结构一致性的异质遥感变更检测
Adaptive Local Structure Consistency based Heterogeneous Remote Sensing Change Detection
论文作者
论文摘要
在自然灾难导致的紧急情况下，异质遥感图像的变更检测是一个重要且具有挑战性的话题。由于异质传感器的不同成像机制，很难直接比较图像。为了应对这一挑战，我们探索了一种基于自适应的局部结构一致性（ALSC）的无监督的变更检测方法，该字母中的异质图像之间的自适应局部结构一致性（ALSC）构建了一个自适应图，该图表代表一个图像域中每个贴片的局部结构，然后将此图在另一个图像域投射到其他图像域以测量变化级别。这种局部结构一致性利用了以下事实：异质图像共享相同地面对象的相同结构信息，这是对模态不变的。为了避免异质数据的泄漏，通过图投影在同一图像域中计算Pixelwise更改图像。实验结果通过与某些最新方法进行比较，证明了所提出的基于ALSC的变更检测方法的有效性。
Change detection of heterogeneous remote sensing images is an important and challenging topic in remote sensing for emergency situation resulting from nature disaster. Due to the different imaging mechanisms of heterogeneous sensors, it is difficult to directly compare the images. To address this challenge, we explore an unsupervised change detection method based on adaptive local structure consistency (ALSC) between heterogeneous images in this letter, which constructs an adaptive graph representing the local structure for each patch in one image domain and then projects this graph to the other image domain to measure the change level. This local structure consistency exploits the fact that the heterogeneous images share the same structure information for the same ground object, which is imaging modality-invariant. To avoid the leakage of heterogeneous data, the pixelwise change image is calculated in the same image domain by graph projection. Experiment results demonstrate the effectiveness of the proposed ALSC based change detection method by comparing with some state-of-the-art methods.
