Optical thickness measurement of occludedsamples by lens-less Fourier transform digitalholography, thermal loading, and machinelearning

Thickness measurements of objects, especially transparent and semi-transparent objects, are essential for theircharacterization and identification. However, in the case of occluded objects, the optical thickness determinationbecomes difficult, and an indirect way must be devised. Thermal loading of the objects changes their opto-thermalproperties, which will be reflected as a change in their optical thickness. The key to quantifying such occludedobjects lies in collecting these opto-thermal signatures. This could be achieved by imaging the changes occurring toa probe wavefront passing through the object while it is being thermally loaded. Digital holographic interferometryis an ideal tool for observing phase changes, as it can be used to compare wavefronts recorded at different instancesof time. Lens-less Fourier transform digital holographic imaging provides the phase information from a singleFourier transform of the recorded hologram and can be used to quantify occluded phase objects. Here we describea technique for the measurement of change in optical thickness of thermally loaded occluded phase samples usinglens-less Fourier transform digital holography and machine learning. The advantage of the proposed technique isthat it is a single shot, lens-less imaging modality for quasi-real-time quantification of phase samples behind thin occlusions