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Remote Sens. 2018, 10(8), 1295; https://doi.org/10.3390/rs10081295

A Spatial-Temporal Adaptive Neighborhood-Based Ratio Approach for Change Detection in SAR Images

1
NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China
2
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
*
Author to whom correspondence should be addressed.
Received: 18 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
(This article belongs to the Special Issue Analysis of Multi-temporal Remote Sensing Images)
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Abstract

The neighborhood-based method was proposed and widely used in the change detection of synthetic aperture radar (SAR) images because the neighborhood information of SAR images is effective to reduce the negative effect of speckle noise. Nevertheless, for the neighborhood-based method, it is unreasonable to use a fixed window size for the entire image because the optimal window size of different pixels in an image is different. Hence, if you let the neighborhood-based method use a large window to significantly suppress noise, it cannot preserve the detail information such as the edge of a changed area. To overcome this drawback, we propose a spatial-temporal adaptive neighborhood-based ratio (STANR) approach for change detection in SAR images. STANR employs heterogeneity to adaptively select the spatial homogeneity neighborhood and uses the temporal adaptive strategy to determine multi-temporal neighborhood windows. Experimental results on two data sets show that STANR can both suppress the negative influence of noise and preserve edge details, and can obtain a better difference image than other state-of-the-art methods. View Full-Text
Keywords: adaptive; change detection; heterogeneity; neighborhood information; ratio operator; synthetic aperture radar (SAR) adaptive; change detection; heterogeneity; neighborhood information; ratio operator; synthetic aperture radar (SAR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Zhuang, H.; Fan, H.; Deng, K.; Yao, G. A Spatial-Temporal Adaptive Neighborhood-Based Ratio Approach for Change Detection in SAR Images. Remote Sens. 2018, 10, 1295.

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