Open AccessComputational LADAR imaging
Author(s) -
Arthita Ghosh,
Maureen K. Powers,
Vishal M. Patel
Publication year - 2017
Publication title -
applied optics
Language(s) - Uncategorized
Resource type - Journals
ISSN - 0003-6935
DOI - 10.1364/ao.56.00b191
Subject(s) - lidar , computer science , speckle pattern , sampling (signal processing) , computer vision , pixel , optics , remote sensing , basis (linear algebra) , radar , azimuth , scan line , artificial intelligence , compressed sensing , image resolution , radar imaging , geology , filter (signal processing) , physics , grayscale , telecommunications , geometry , mathematics
Most LADAR (laser radar, LIDAR) imaging systems use pixel-basis sampling, where each azimuth and elevation resolution element is uniquely sampled and recorded. We demonstrate and examine alternative sampling and post-detection processing schemes where recorded measurements are made in alternative bases that are intended to reduce system power consumption and laser emissions. A prototype of such a sensor having the capability to generate arbitrary illumination beam patterns rather than spot, line scanning, or flash techniques is described along with computational imaging algorithms to reduce speckle and identify scene objects in a low-dimensional compressed basis rather than in the pixel basis. Such techniques yield considerable energy savings and prove valuable when used on platforms with severe limitations on sensor size, weight, and power, and in particular as part of autonomous systems where image output for human interpretation is unnecessary.