Paper
14 May 2015 See-through obscurants via compressive sensing in degraded visual environment
Richard C. Lau, T. K. Woodward
Author Affiliations +
Abstract
This paper proposes a new approach for seeing through obscurants in a severe degraded visual environment (DVE). The proposed method allows extraction of hidden information from the raw sensor data via computational imaging technologies. We show that although to the human eye a sensor captures a zero-visibility view of an object through dense obscurants, it is possible to recover the hidden visual information of the object and display its visual cue to the aircraft pilot to aid in landing and maneuvering. The proposed approach uses a compressive sensing algorithm incorporating an over-complete dictionary composed of pose transformation of the targeted object. Information on the recovered image is used in a feedback loop to further remove perception noise and maintain tracking of the object from a moving aircraft. The proposed algorithm is sensor agnostic and can be applied to images taken from Infrared, LIDAR, or RF imagery sensors. We quantify the upper bound of the DVE noise in which the proposed method is effective via simulation results.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard C. Lau and T. K. Woodward "See-through obscurants via compressive sensing in degraded visual environment", Proc. SPIE 9484, Compressive Sensing IV, 94840F (14 May 2015); https://doi.org/10.1117/12.2178039
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Driver's vision enhancers

Visualization

Associative arrays

Compressed sensing

Sensors

Signal to noise ratio

Detection and tracking algorithms

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