Multiscale directional filtering of noisy InSAR phase images

In this work, we present a new approach for the problem of interferometric phase noise reduction in synthetic aperture radar interferometry based on the shearlet representation. Shearlets provide a multidirectional and multiscale decomposition that have advantages when dealing with noisy phase fringes over standard filtering methods. Using a shearlet decomposition of a noisy phase image, we can adaptively estimate a phase representation in a multiscale and anisotropic fashion. Such denoised phase interferograms can be used to provide much better digital elevation maps (DEM). Experiments show that this method performs significantly better than many competitive methods.