A new approach to apply compressive sensing to LIDAR sensing

Richard C. Lau; T. K. Woodward

doi:10.1117/12.2058777

23 May 2014 A new approach to apply compressive sensing to LIDAR sensing

Richard C. Lau, T. K. Woodward

Proceedings Volume 9109, Compressive Sensing III; 91090U (2014) https://doi.org/10.1117/12.2058777
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

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.

Citation Download Citation

Richard C. Lau and T. K. Woodward "A new approach to apply compressive sensing to LIDAR sensing", Proc. SPIE 9109, Compressive Sensing III, 91090U (23 May 2014); https://doi.org/10.1117/12.2058777

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