Abstract
In this paper, we propose a novel methodology for Change Detection between two monovariate complex SAR images. Linear Time-Frequency tools are used in order to recover a spectral and angular diversity of the scatterers present in the scene. This diversity is used in bi-date change detection framework to develop a detector, whose performances are better than the classic detector on monovariate SAR images.
Highlights
In Remote Sensing, CD (Change detection) consists in using several images in order to detect or measure the changes occurring in a scene of interest
We call these, colored scatterers. This spectral and angular non-stationary behaviour of scatterers can be due to their material, orientation or geometry. This spectral and angular diversity is interesting in the problematic of CD on monovariate images
We propose in this paper to take advantage of this methodology, in the CD framework, in order to perform the multivariate algorithms using spectral and angular diversity
Summary
In Remote Sensing, CD (Change detection) consists in using several images in order to detect or measure the changes occurring in a scene of interest. Recent works have been done to extend the monovariate algorithms in the multivariate case [3], [4], [5], [6] Those works exploit polarimetric diversity to improve the CD results. We assume that the scatterers present in the scene will respond to an electromagnetic wave in all directions and in all frequencies This hypothesis is reasonable for low-resolution SAR systems, but it was shown ([7], [8], [9], [10], [11], [12]) that for recent high-resolution SAR imagery, it does no longer apply. This spectral and angular non-stationary behaviour of scatterers can be due to their material (dispersive), orientation (anisotropic) or geometry (anisotropic and dispersive) This spectral and angular diversity is interesting in the problematic of CD on monovariate images.
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