Image mosaicking and seam reduction of InSAR-derived Active-Layer Thickness Distributions



The aim of this project was to extend various image processing techniques towards an area of active research in the geophysical climate community. Interferometric synthetic aperture radar (InSAR) is a well-established radar remote sensing technique. The synthetic aperture radar (SAR) technique utilizes the principle of coherent radar pulse integration, and doppler processing to generate highresolution (~5-10 m pixel resolution) radar images of the earth’s surface from earth-orbiting satellites. Each pixel in a SAR image is a complex variable with an amplitude associated with the amount of returned scattered energy from the earth’s surface that is received by the radar, and a phase associated with the total distance from the radar unit to the earth’s surface. When multiple SAR images over a single region of interested are acquired, the (element-wise) product of one image with the complex conjugate of the other image yields the difference in phase between these two images. Because this phase is directly related to distance, this image of

phase differential (hereafter referred to as an interferogram), encapsulates information related to the earth’s topography, and any surface deformation that occurred in-between the acquisition times of the two images (citation needed). If a priori information of the earth’s topography is available (conventionally a digital elevation model, or DEM), the topographic phase dependency can be removed from an interferogram, leaving behind the surface deformation signature and noise.

Some image enhancement methods

Computing similarity between query image and target database



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