Shin, DongeekShapiro, Jeffrey H.Goyal, Vivek K.2020-01-282020-01-282017-10-10D. Shin, J.H. Shapiro, V. Goyal. 2017. "Photon-Efficient Super-Resolution Laser Radar." Proceedings Volume 10394, Wavelets and Sparsity XVII; 1039409 (2017) https://doi.org/10.1117/12.2273208https://hdl.handle.net/2144/39195The resolution achieved in photon-efficient active optical range imaging systems can be low due to non-idealities such as propagation through a diffuse scattering medium. We propose a constrained optimization-based frame- work to address extremes in scarcity of photons and blurring by a forward imaging kernel. We provide two algorithms for the resulting inverse problem: a greedy algorithm, inspired by sparse pursuit algorithms; and a convex optimization heuristic that incorporates image total variation regularization. We demonstrate that our framework outperforms existing deconvolution imaging techniques in terms of peak signal-to-noise ratio. Since our proposed method is able to super-resolve depth features using small numbers of photon counts, it can be useful for observing fine-scale phenomena in remote sensing through a scattering medium and through-the-skin biomedical imaging applications.OpticsDeconvolutionDepth imagingInverse problemLaser radarPhoton countingSuper-resolutionConference materials10.1117/12.2273208293326