Feature enhancement for multi-polarimetric SAR images: A novel approach based on PDE and regularization
Xintong Tan, Jubo Zhu · 2017
This paper aims at the feature enhancement for multi-polarimetric synthetic aperture radar (SAR) images. A novel approach based on PDE and regularization which is an extension of the original PDE and regularization methods is proposed. It contains the PDE term for speckle suppression and the sparsity constraint term for strong scatter enhancement. The PDE term is established by combining the ROA detected operator and the amplitude of the multi-polarimetric SAR images. The sparsity constraint term contains the structural information and the sparsity of the images. Experiments on the measured multi-polarimetric SAR images show that the proposed approach can efficiently suppress speckle noise and enhance features especially structural and edge features in SAR images.