2D signal estimation for sparse distributed target photon counting data
Matthew Hayman,
Robert A. Stillwell,
Josh Carnes
et al.
Abstract:In this study, we explore the utilization of penalized likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifically, we adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally… Show more
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