Abstract. Feature specific imaging is a computational imaging technique that minimizes the number of measurements needed to sufficiently reconstruct a scene by using a priori knowledge (e.g., the scene's second-order statistics) to judiciously, as well as possibly adaptively, choose the projection vectors to be measured. Here, we have developed an approach to three-dimensional adaptive feature specific imaging that takes into account the obstruction of distant objects by closer objects in the adaption of the projections and in the reconstruction algorithm. The developed system reconstructs the cross-range image of the scene at each range bin from a set of range resolved measurements from all the return from the scene at that range using only a single photodetector, while adapting to the obstruction of the scene by closer objects. Simulations and a proof-of-concept demonstration of adaptive three-dimensional feature specific imaging are presented.
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