Scattering Coefficients of Inhomogeneous Objects and Their Application in Target Classification in Wave Imaging
This work addresses target classification in wave imaging for inhomogeneous objects, but the approach is incremental as it combines existing scattering coefficient extraction with dictionary matching.
The paper proposes a procedure for target classification in wave imaging using scattering coefficients to build frequency-dependent distribution descriptors, and tests it numerically with measurement noise, achieving identification of inhomogeneous targets from a dictionary.
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.