The effect of speckle reduction on coherence estimation and interferometric phase of InSAR

Abstract

Synthetic aperture radar (SAR) images always suffer from strongly speckle noise, which is a great obstacle to coherence (or correlation coefficient) estimation and interferometric phase, furthermore hinders the accuracy of phase unwrapping and information extraction with SAR interferometry (InSAR) technique. In this article, we propose to suppress the speckle of SAR images with several self-adaptive filtering methods so as to evaluate how the filtering influences the coherence and the quality of phase map by quantitative and qualitative analysis. As an example, ERS SAR interferometric pair covering Shanghai is used for this study. The filtering algorithms we adopted include enhanced Lee, enhanced Frost, Gamma Map, and Kuan filtering, etc. In order to choose the optimal algorithm, we used four kinds of technical criterions, such as smoothness index, speckle noise index, equivalent number of looks (ENL), and normalized mean, etc. By comparing the former criterions, we can determine which kind of filtering will be used in the following data processing. Once the appropriate filtering is determined, we thus could move on and carry on operations of corigistration, Phase Conjugate multiplication, and flat earth phase removal, etc. Finally, we have got the coherence and interferometric phase maps by using the unfiltered and filtered interferometric pairs, respectively. The mean, standard derivation (SD), and statistical distribution chart are used to estimate the change of coherence. The mean, SD, and sum of phase difference (SPD) are adopted to evaluate the quality of interferometric phase map. The results show that the speckle reduction did not improve the quality of interferometric phase map and nearly have no impact on the coherence coefficients. The next study is which kind of other measures should be adopted under the condition of small temporal and spatial baseline in the interferometry.