23 May 2014 A new approach to apply compressive sensing to LIDAR sensing
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Recently, Compressive Sensing (CS) has been successfully applied to multiple branches of science. However, most CS methods require sequential capture of a large number of random data projections, which is not advantageous to LIDAR systems, wherein reduction of 3D data sampling is desirable. In this paper, we introduce a new method called Resampling Compressive Sensing (RCS) that can be applied to a single capture of a LIDAR point cloud to reconstruct a 3- dimensional representation of the scene with a significant reduction in the required amount of data. Examples of 50 to 80% reduction in point count are shown for sample point cloud data. The proposed new CS method leads to a new data collection paradigm that is general and different from traditional CS sensing such as the single-pixel camera architecture.
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Richard C. Lau, Richard C. Lau, T. K. Woodward, T. K. Woodward, } "A new approach to apply compressive sensing to LIDAR sensing", Proc. SPIE 9109, Compressive Sensing III, 91090U (23 May 2014); doi: 10.1117/12.2058777; https://doi.org/10.1117/12.2058777

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