A fast and reliable change detection feature from bi-temporal amplitude SAR images

In this paper, we propose a change detection feature for an amplitude SAR image pair, based on both information theoretic (IT) assumptions and a CFAR criterion derived from the probabilistic model of the ratio image. In particular, the proposed method aims to introduce two main improvements with respect to the previous IT-based approaches. The first goal is to find a strategy to adaptively quantize the 2-D scatterplot instead of applying clustering. This is carried out by performing a preliminary partition of the image pixels according to a constant false alarm rate criterion that is based on the probabilistic model of the ratio image. The second goal is to test the proposed method in order to assess reliable performances in case of severe speckle noise and in case of small percentage of change within the scene. Therefore, experimental results have been carried out with simulated changes applied to synthetically-generated 1-look SAR images produced from an optical remote sensing image. True Cosmo-SkyMed SAR images have been also considered on a damage assessment scenario.