Photon efficient super resolution laser radar
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.
Optical Engineering Applications