InSAR Phase Unwrapping Algorithm Based on Deep GAN

At present, the traditional phase unwrapping algorithm is difficult to balance accuracy and efficiency. The efficiency in experiments of simulated measured topographic interferograms. In this paper, technology will be studied under framework deep learning theory according development trend InSAR intelligence. A based on GAN proposed. model structure includes dense convolution layer blocks series structure, so that network can achieve a better between feature extraction detail preservation interferogram. This helpful improve training network. experimental results show has good expansion effect interferogram with high signal-to-noise ratio. synthesis makes full use advantages branch cutting method finite element method. reliable region unreliable are determined, transmission error from effectively avoided. ensured, overall convergence greatly improved.