Gradient based SAR image despeckling and super resolution using Zernike Moments and Bootstrapping
Yaser Arianpour, Hamidreza R. Amindavar, James A. Ritcey · 2017
In this paper, we propose a new despeckling and super resolution (SR) approach for synthetic aperture radar (SAR) applications. In our method, we transfers the speckled low resolution SAR image to gradient domain and extract all of edges with their sharpness. Then, using Zernike Moments and also Bootstrapping approach we obtains the new values for edges sharpness. By these new edges sharpness and after using the modified gradient field transformation, image reconstruction leads to noise-free high resolution images with better quality than traditional methods.