A Recursive Born Approach to Nonlinear Inverse Scattering
Machine Learning
2016-08-24 v1 Optics
Abstract
The Iterative Born Approximation (IBA) is a well-known method for describing waves scattered by semi-transparent objects. In this paper, we present a novel nonlinear inverse scattering method that combines IBA with an edge-preserving total variation (TV) regularizer. The proposed method is obtained by relating iterations of IBA to layers of a feedforward neural network and developing a corresponding error backpropagation algorithm for efficiently estimating the permittivity of the object. Simulations illustrate that, by accounting for multiple scattering, the method successfully recovers the permittivity distribution where the traditional linear inverse scattering fails.
Cite
@article{arxiv.1603.03768,
title = {A Recursive Born Approach to Nonlinear Inverse Scattering},
author = {Ulugbek S. Kamilov and Dehong Liu and Hassan Mansour and Petros T. Boufounos},
journal= {arXiv preprint arXiv:1603.03768},
year = {2016}
}