scholarly journals Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm

2017 ◽  
Author(s):  
Caihong Mu ◽  
Chengzhou Li ◽  
Yi Liu ◽  
Menghua Sun ◽  
Licheng Jiao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Change Detection ◽  
Sar Images

River ice monitoring and change detection with multi-spectral and SAR images: application over yellow river

2021 ◽  
Author(s):  
Xiuwei Zhang ◽  
Yuanzeng Yue ◽  
Lin Han ◽  
Fei Li ◽  
Xiuzhong Yuan ◽  
...  
Keyword(s):  
Change Detection ◽  
Yellow River ◽  
River Ice ◽  
Sar Images

scholarly journals Patch-Based Change Detection Method for SAR Images with Label Updating Strategy

2021 ◽  
Vol 13 (7) ◽  
pp. 1236
Author(s):  
Yuanjun Shu ◽  
Wei Li ◽  
Menglong Yang ◽  
Peng Cheng ◽  
Songchen Han
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Change Detection ◽  
Detection Method ◽  
Training Data ◽  
Synthetic Aperture ◽  
Learning Method ◽  
Sar Images ◽  
Two Stage ◽  
Second Stage

Convolutional neural networks (CNNs) have been widely used in change detection of synthetic aperture radar (SAR) images and have been proven to have better precision than traditional methods. A two-stage patch-based deep learning method with a label updating strategy is proposed in this paper. The initial label and mask are generated at the pre-classification stage. Then a two-stage updating strategy is applied to gradually recover changed areas. At the first stage, diversity of training data is gradually restored. The output of the designed CNN network is further processed to generate a new label and a new mask for the following learning iteration. As the diversity of data is ensured after the first stage, pixels within uncertain areas can be easily classified at the second stage. Experiment results on several representative datasets show the effectiveness of our proposed method compared with several existing competitive methods.

scholarly journals Change detection in SAR images based on iterative Otsu

2020 ◽  
Vol 53 (1) ◽  
pp. 331-339
Author(s):  
Shuwen Xu ◽  
Yan Liao ◽  
Xueying Yan ◽  
Gang Zhang
Keyword(s):  
Change Detection ◽  
Sar Images

A Novel SAR Images Change Detection Method Based on Dynamic TUNET-CRF Model

2021 ◽  
Author(s):  
Jianlong Zhang ◽  
Mengying Cui ◽  
Bin Wang ◽  
Chen Chen ◽  
Yang Zhou ◽  
...  
Keyword(s):  
Change Detection ◽  
Detection Method ◽  
Sar Images

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

2018 ◽  
Vol 10 (8) ◽  
pp. 1295 ◽  
Author(s):  
Huifu Zhuang ◽  
Hongdong Fan ◽  
Kazhong Deng ◽  
Guobiao Yao
Keyword(s):  
Change Detection ◽  
Window Size ◽  
Speckle Noise ◽  
Adaptive Strategy ◽  
Negative Influence ◽  
Sar Images ◽  
Spatial Homogeneity ◽  
Difference Image ◽  
Negative Effect ◽  
Adaptive Neighborhood

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.

scholarly journals COHERENT CHANGE DETECTION FOR REPEATED-PASS INTERFEROMETRIC SAR IMAGES: AN APPLICATION TO EARTHQUAKE DAMAGE ASSESSMENT ON BUILDINGS

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 383-388 ◽  
Author(s):  
D. Oxoli ◽  
P. Boccardo ◽  
M. A. Brovelli ◽  
M. E. Molinari ◽  
A. Monti Guarnieri
Keyword(s):  
Change Detection ◽  
Emergency Management ◽  
Performance Assessment ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Detection Sensitivity ◽  
Management Service ◽  
Sar Images ◽  
Coherent Change Detection ◽  
Interferometric Sar

<p><strong>Abstract.</strong> During disaster response, the availability of relevant information, delivered in a proper format enabling its use among the different actors involved in response efforts, is key to lessen the impact of the disaster itself. Focusing on the contribution of geospatial information, meaningful advances have been achieved through the adoption of satellite earth observations within emergency management practices. Among these technologies, the Synthetic Aperture Radar (SAR) imaging has been extensively employed for large-scale applications such as flood areas delineation and terrain deformation analysis after earthquakes. However, the emerging availability of higher spatial and temporal resolution data has uncovered the potential contribution of SAR to applications at a finer scale. This paper proposes an approach to enable pixel-wise earthquake damage assessments based on Coherent Change Detection methods applied to a stack of repeated-pass interferometric SAR images. A preliminary performance assessment of the procedure is provided by processing Sentinel-1 data stack related to the 2016 central Italy earthquake for the towns of Ametrine and Accumoli. Damage assessment maps from photo-interpretation of high-resolution airborne imagery, produced in the framework of Copernicus EMS (Emergency Management Service &amp;ndash; European Commission) and cross-checked with field survey, is used as ground truth for the performance assessment. Results show the ability of the proposed approach to automatically identify changes at an almost individual building level, thus enabling the possibility to empower traditional damage assessment procedures from optical imagery with the centimetric change detection sensitivity characterizing SAR. The possibility of disseminating outputs in a GIS-like format represents an asset for an effective and cross-cutting information sharing among decision makers and analysts.</p>

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