Feature enhancement of InSAR imaging using joint sparse constraints of magnitude and phase

In this paper, a novel algorithm of joint sparse regularization of magnitude and interferometric phase for InSAR imaging is proposed to achieve features enhancement. Based on the established complex phase noise model, the joint optimization problem for InSAR imaging is achieved from maximum a posterior (MAP) estimation that exploits the statistic of complex images in wavelet domain. The proposed algorithm provides the benefits of interferometric phase noise reduction. Finally, experimental results based on simulated-data confirm the validation of the proposal.