A keypoint approach for change detection between SAR images based on graph theory

机译：基于图论的SAR图像间变化检测关键点方法

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摘要

This paper investigates the problem of change detection in multitemporal Synthetic Aperture Radar (SAR) images. Our proposition is to perform a keypoint-based algorithm to detect land-cover changes between two SAR images employing the graph theory combined with the log-ratio operator. First, a set of feature points is extracted from one of the two images. A weighted graph is then constructed to connect these keypoints based on their similarity measures from this first image. Based on this graph, our motivation is to measure the coherence between the information carried by the two images. In other words, the change level will depend on how much the second image still conforms to the graph constructed from the first image. Furthermore, due to the presence of speckle noise, the log-ratio operator will be exploited to replace the image difference operator. Experiments performed on real SAR images using the proposed algorithm provide very promising and competitive results compared to classical methods.

机译：本文研究了多时相合成孔径雷达（SAR）图像中的变化检测问题。我们的建议是使用图论结合对数比算子，执行基于关键点的算法来检测两个SAR图像之间的土地覆盖变化。首先，从两个图像之一中提取一组特征点。然后，根据这些关键点的相似度度量值，构造一个加权图来连接这些关键点。基于此图，我们的动机是测量两个图像承载的信息之间的相干性。换句话说，变化水平将取决于第二图像仍然符合从第一图像构造的图的多少。此外，由于斑点噪声的存在，将使用对数比算子来代替图像差算子。与经典方法相比，使用提出的算法在真实SAR图像上进行的实验提供了非常有希望的竞争结果。

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来源
《2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images》|2015年|1-4|共4页
会议地点 Annecy(FR)
作者
Minh-Tan Pham; Mercier Gregoire; Michel Julien;
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TELECOM Bretagne, Brest, France;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Change detection; SAR images; graph theory; keypoint approach; log-ratio operator;

机译：变化检测; SAR图像;图论;关键点法;对数比算子;

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专利

1. Change Detection Between SAR Images Using a Pointwise Approach and Graph Theory [J] . M. T. Pham, G. Mercier, J. Michel IEEE Transactions on Geoscience and Remote Sensing . 2016,第4期

机译：使用逐点方法和图论的SAR图像之间的变化检测
2. Unsupervised SAR Image Change Detection Based on SIFT Keypoints and Region Information [J] . Yan Wang, Lan Du, Hui Dai IEEE Geoscience and Remote Sensing Letters . 2016,第7期

机译：基于SIFT关键点和区域信息的无监督SAR图像变化检测
3. Change detection in SAR images using deep belief network: a new training approach based on morphological images [J] . Samadi Farnaam, Akbarizadeh Gholamreza, Kaabi Hooman Image Processing, IET . 2019,第12期

机译：基于深度信念网络的SAR图像变化检测：一种基于形态学图像的训练新方法
4. A keypoint approach for change detection between SAR images based on graph theory [C] . Minh-Tan Pham, Mercier Gregoire, Michel Julien International Workshop on the Analysis of Multitemporal Remote Sensing Images . 2015

机译：基于图论的SAR图像改变检测的关键点方法
5. Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters. [D] . Ajadi, Olaniyi A. 2017

机译：SAR影像的无监督多尺度变化检测，用于监视自然和人为灾难。
6. Fast SAR Image Change Detection Using Bayesian Approach Based Difference Image and Modified Statistical Region Merging [O] . Han Zhang, Weiping Ni, Weidong Yan, -1

机译：基于贝叶斯方法的差分图像和改进的统计区域合并的快速SAR图像变化检测
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A keypoint approach for change detection between SAR images based on graph theory

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