Coherence Estimation from Multilook Detected SAR Images (Invited Paper)

This work presents an unsupervised method capable to provide estimates of temporal coherence starting from a couple of multilook detected SAR images of the same scene. The method relies on a robust measurement of the temporal correlation of speckle patterns occurring between the two pass dates. Thanks to the accurate speckle assessment, the temporal correlation coefficient (TCC) of speckle between two overlapped images taken different times is estimated. A nonlinear transformation aimed at decorrelating the data across time while retaining the multiplicative noise model is defined starting from the pixel geometric mean and ratio of the two overlapped observations. Such a reversible transformation is is applied to the couple of images to expedite assessment of temporal speckle patterns correlation. The TCC of speckles is estimated from the noise variances of a transformed couple of images by inverting the relationship yielding the noise variances of the transformed data. Experiments are carried out on two SAR observations from the ERS-1/2 Tandem mission. Starting from the SLC pair, coherence is first estimated to be used as reference. Then, detected 5-looks images are produced and TCC is measured on square blocks, to yield the desired coherence estimate. A linear regression fit shows a good degree of matching with the true coherence values, which holds also on textured areas. Experiments show a good degree of accuracy, when the TCC of speckles is estimated on 32 × 32 blocks of the geometric mean and ratio of detected 5-looks amplitude images. The method yields acceptable results also in the presence of strong reflectors and textures (urban area) where intensity-based coherence estimators generally fail.