Photon-efficient super-resolution laser radar

• Main Authors: Shin, Dongeek (Contributor), Shapiro, Jeffrey H (Contributor), Goyal, Vivek K (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor)
• Format: Article
• Language: English
• Published: SPIE-Intl Soc Optical Eng, 2018-06-25T18:11:16Z.
• Subjects: Article
• Online Access: Get fulltext

The 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.
Samsung Scholarship Foundation
National Science Foundation (U.S.) (Grant 1161413)
National Science Foundation (U.S.) (Grant 1422034)