LIDAR WAVEFORM MODELING USING A MARKED POINT PROCESS

Abstract : Lidar waveforms are 1D signal consisting of a train of echoes where each of them correspond to a scattering target of the Earth surface. Modeling these echoes with the appropriate parametric function is necessary to retrieve physical information about these objects and characterize their properties. This paper presents a marked point process based model to reconstruct a lidar signal in terms of a set of parametric functions. The model takes into account both a data term which measures the coherence between the models and the waveforms, and a regularizing term which introduces physical knowledge on the reconstructed signal. We search for the best configuration of functions by performing a Reversible Jump Markov Chain Monte Carlo sampler coupled with a simulated annealing. Results are finally presented on different kinds of signals in urban areas.
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Clément Mallet, Florent Lafarge, Frederic Bretar, Uwe Soergel, Christian Heipke. LIDAR WAVEFORM MODELING USING A MARKED POINT PROCESS. International Conference on Image Processing (ICIP), Nov 2009, Cairo, Egypt. ⟨hal-00781804⟩

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