Polarimetric SAR Change Detection With the Complex Hotelling–Lawley Trace Statistic

Abstract

Abstract-In this paper, we propose a new test statistic for unsupervised change detection in polarimetric radar images. We work with multilook complex covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex-kind Hotelling-Lawley trace statistic for measuring the similarity of two covariance matrices. The distribution of the Hotelling-Lawley trace statistic is approximated by a Fisher-Snedecor distribution, which is used to define the significance level of a false alarm rate regulated change detector. Experiments on simulated and real PolSAR data sets demonstrate that the proposed change detection method gives detections rates and error rates that are comparable with the generalized likelihood ratio test.

A Method of Time-Series Change Detection Using Full Polsar Images From Different Sensors

“…Although the traditional pixel-based unsupervised change detection method using bi-temporal PolSAR images can detect the change between two different times with same sensor (Akbari, 2016), they could not detect the total changes of the entire time series from different sensors . To solve these problems, some researchers simply compared the pair-wise images in the time-series images and detected the time-series change, which suffers from some deficiencies, such as it is time-consuming and couldn't detect some small continuous changes .…”

A Novel Method of Change Detection in Bi-Temporal PolSAR Data Using a Joint-Classification Classifier Based on a Similarity Measure

“…These methods are usually applied in multi-temporal single-channel SAR-based change detection. Unlike the above methods, test statistics can be applied in not only single-channel SAR data, but also PolSAR data [5,27,28]. The use of multichannel data (coherency or covariance matrix) can obtain a more accurate comparison image.…”

An Unsupervised Method of Change Detection in Multi-Temporal PolSAR Data Using a Test Statistic and an Improved K&I Algorithm

“…Because SAR is an active microwave sensor with all-weather, day-and-night operational imaging capability [8], the use of SAR sensors instead of optical sensors is attractive in change detection studies [9]. Recently, many researchers have focused 2 of 22 on change detection and time-series analysis based on SAR images [10][11][12].…”

“…Compared with single-channel SAR images, polarimetric SAR (PolSAR) sensors acquire phase and amplitude information in different polarizations, and thus offer more scattering information [17,18]. However, literature on change detection with PolSAR data is sparse [9]. Because of the potential to provide improved detection capability and to extend the application of PolSAR data in change detection, we explore multi-temporal PolSAR data for change detection in this study.…”

“…In general, unsupervised change detection in SAR images includes three steps: (1) preprocessing, (2) generating the comparison image (CI), and (3) making a decision based on the analysis of the CI in order to obtain the binary change map [9,18]. The preprocessing of multi-temporal SAR images is a critical step in the change detection and involves radiometric calibration, image co-registration, and speckle filtering.…”