Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
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In this paper we present several methods for change detection in a pair of multi-look synthetic aperture radar (SAR) images of the same scene. We implement and compare several techniques which vary in complexity. Among the simple methods that are implemented are differencing, Euclidean distance, and image ratioing. These methods require minimal processing time, with little computational complexity, and incorporate no statistical information. We also implemented methods which incorporate second order statistic calculations in making a change decision in efforts to mitigate false alarms arising from the speckle noise, misregistration errors, and nonlinear variations in SAR images. These methods include a Wiener prediction-based method, Mahalanobis distance measure and subspace projection method. We compare the performance of these methods using multilook SAR images containing several targets (mines). We present results in the form of receiver operating characteristics (ROC) curves.