Scattering Coefficients of Inhomogeneous Objects and Their Application in Target Classification in Wave Imaging

TL;DR

This paper introduces a method for classifying inhomogeneous objects in wave imaging by using scattering coefficients to create a dictionary of descriptors, enabling accurate identification despite measurement noise.

Contribution

It presents a novel procedure that extracts scattering coefficients and constructs a frequency-dependent dictionary for target classification in wave imaging.

Findings

Effective classification with noisy data

Robust matching algorithm for target identification

Validated approach through numerical tests

Abstract

The aim of this paper is to provide and numerically test in the presence of measurement noise a procedure for target classification in wave imaging based on comparing frequency-dependent distribution descriptors with precomputed ones in a dictionary of learned distributions. Distribution descriptors for inhomogeneous objects are obtained from the scattering coefficients. First, we extract the scattering coefficients of the (inhomogeneous) target from the perturbation of the echoes. Then, for a collection of inhomogeneous targets, we build a frequency-dependent dictionary of distribution descriptors and use a matching algorithm in order to identify a target from the dictionary up to some translation, rotation and scaling.