Independency Preserving DependentMaximum Likelihood Texture Tracking Model

Glacier velocity monitoring by coherent techniques has been affected by speckle decorrelation that results in a phase stability problem. To overcome this limitation, it is very common to estimate the glacier flow with normalize cross correlation (NCC) technique using amplitude images. However, NCC is not the maximum likelihood (ML) estimate for SAR amplitude images, it is only ML solution for optical data with additive noise model and for complex SAR data with circular Gaussian statistics. Related to this problem, the maximum likelihood motion estimation technique is re-defined for amplitude images with taking care to its speckle model. In addition to monitor the flow of glacier by single-channel SAR system, investigation of suitability of the proposed technique for multi-channel SAR system is the second aim of this study. This study has shown that the proposed technique can be continuously performed with the aim of velocity monitoring without any assumption concerning data sets' independence.