Absorption Based Optical Imaging of Dispersion Processes

We consider the problem of fitting atmospheric dispersion parameters from time-resolved back-scattered differential absorption Lidar (DIAL) measurements. A clear advantage of optical remote sensing modalities is an extended range which makes them less sensitive to strictly local perturbations/modelling errors or the distance to a plume source. In contrast to other state-of-the-art DIAL methods, we don’t make a single scattering assumption but propose the collection of multiply scattered photons from wider/multiple fields-of-view that can aid in the reconstruction of certain image features. The behaviour of photons in heterogeneous scattering media is modelled through the time dependent Radiative Transfer Equation (RTE) which drastically increases the computational complexity compared current DIAL based approaches. Motivated by environmental emergency response applications and the need to solve the problem in nearly real-time, we address this issue by reconstructing dispersion parameters instead of a voxel-representation associated to an image. The resulting method avoids a high-dimensional inverse problem that is typical for 3D imaging problems and yields a natural regularisation mechanism which is needed when a solution of the otherwise ill-posed inverse problem must be computed from low signal-to-noise data. The obtained parameters have meaningful physical units while spatial concentrations can be obtained by means of forward evaluation of the dispersion process.