Perturbations worked as extra scatters will cause coda waveform distortions; thus, coda wave with long propagation time and traveling path are sensitive to micro-defects in strongly heterogeneous media such as concretes. In this paper, we conduct varied external loads on a life-size concrete slab which contains multiple existing micro-cracks, and a couple of sources and receivers are installed to collect coda wave signals. The waveform decorrelation coefficients (DC) at different loads are calculated for all available source-receiver pair measurements. Then inversions of the DC results are applied to estimate the associated distribution density values in three-dimensional regions through kernel sensitivity model and least-square algorithms, which leads to the images indicating the micro-cracks positions. This work provides an efficiently non-destructive approach to detect internal defects and damages of large-size concrete structures.
An important task for remote sensing applications is the characterization of material properties, which can be accomplished by estimating physics-based parameters from optical scattering off a target’s surface. In this paper, a novel approach is described to generate parameter-based images by applying the modified polarimetric bidirectional reflectance distribution function (pBRDF) model to the polarimetric imaging measurements collected with the University of Arizona’s Ground Multiangle SpectroPolarimetric Imager (Ground-MSPI). Values for complex refractive index (η), slope variance roughness (σ<sup>2</sup>) and diffuse scattering coefficient (ρ<sub>d</sub>) for each pixel are jointly estimated. Images consisting of the parameter values are generated by using the estimation results and optimized by contrast-ratio enhancement algorithms. The approach offers significant potential for remote targets analysis and novel imaging technology development.