We consider the phase noise filtering problem for interferometric synthetic aperture radar(InSAR)based on the dictionary learning technique.Due to the non-convexity of the optimization problem is difficult to solve.By using the splitting technique and employing the augmented Lagrangian framework,we obtain a relaxed nonlinear constraint optimization problem with l_1-norm regularization which can be solved efficiently by the alternating direction method of multipliers(ADMM).Specifically,we firstly train dicti...
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