Coherent Change Detection (CCD) using multi-temporal Synthetic Aperture Radar (SAR) is one of the most important applications of remote sensing technology. With the advent of high-resolution SAR images, CCD has received a lot of attention. In CCD, the interferometric coherence between two SAR images is evaluated and analyzed to detect surface changes. Unfortunately, the sample coherence estimator is biased, especially for low-coherence values. The consequence of this bias is the apparition of highly coherent pixels inside the changed area. Within this context, the detection performance will considerably degrade, particularly when using high resolution SAR data. In this paper, we propose a new CCD method based on cleaning of coherence inside changed areas, which is characterized by high Local Fringe Frequencies (LFF) values, followed by a space-averaged coherence method. According to the proposed method, the results obtained with Cosmo-SkyMed (CSK) SAR data show an enhancement of change detection performance of about 6% while preserving subtle changes.
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