The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1369–1375, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1369-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1369–1375, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1369-2022
 
31 May 2022
31 May 2022

A WEIGHTED COHERENCE ESTIMATOR FOR COHERENT CHANGE DETECTION IN SYNTHETIC APERTURE RADAR IMAGES

M. Wang1, G. Huang2, J. Zhang3, F. Hua4, and L. Lu2 M. Wang et al.
  • 1School of Environment and Spatial Informatics, China Univ. of Mining and Technology, 1 Daxue Road, Xuzhou, China
  • 2Chinese Academy of Surveying and Mapping, Beijing, China
  • 3National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing, China
  • 4Jiangsu Normal Univ., Xuzhou, China

Keywords: Coherence Estimator, Coherent Change Detection, Maximum Likelihood, Synthetic Aperture Radar, Weighted Estimator

Abstract. Synthetic aperture radar (SAR) coherent change detection (CCD) often utilizes the degree of coherence to detect changes that have occurred between two data collections. Although having shown some performances in change detection, many existing coherence estimators are still relatively limited because the change areas do not stand out well from all decorrelation areas due to the low cluster-to-noise ratio (CNR) and volume scattering. Moreover, many estimators require the equal-variance assumption between two SAR images of the same scene. However, the assumption is less likely to be met in regions of significant differences in intensity, such as the change areas. To address these problems, we proposed an improved coherence estimator that introduces the parameters about the true-variance ratio as the weights. Since these parameters are closely related to the ratio-change statistic in intensity-based change detection algorithms, their introduction frees the estimator from the need for the equal-variance assumption and enables detection results to largely combine the advantages of intensity-based and CCD methods. Experiments on simulated and real SAR image pairs demonstrate the effectiveness of the proposed estimator in highlighting the change, obviously improving the contrast between the change and the background.