Share Email Print

Proceedings Paper

Introduction to analysis of errors inherent in multispectral imaging through the sea surface 2: sensor and interfacial effects
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Multispectral and hyperspectral sensing are key techniques in the airborne detection of submerged objects such as jettisoned contraband, unexploded ordnance, and sea mines. Unfortunately, the errors incurred by imaging through the sea surface (also called imaging trans-MBL or through the marine boundary layer) include spatial, spectral, and temporal distortions. In Part I of this two-part series, we showed that spatial distortions derive primarily from projection errors resulting from refraction at the air-sea interface. In practice, the variability and uncertainty of in situ measurements of aqueous refractive index pose a problem for accurate prediction of such projection errors. We also discussed problems that arise due to target variability, surface contamination, and target surface corruption due to corrosion. In this paper, we summarize spatial distortions due to imaging with intensified cameras, as well as spectral errors that result from interaction of sensor optics with the environment (e.g., thermal drift in spectral filter frequency response). We discuss the spatial effects of detector noise and error, and summarize anomalies observed in our recent study of intensified multispectral camera circuitry. We briefly review the effects of interfacial refraction and in-water scattering upon the spatial clarity and resolution of submerged target imagery. We conclude our development with an error budget that is configured for several common sensing scenarios (e.g., staring-array and pushbroom sensors), then discuss effects of decorrelation between spectral, spatial, and temporal variables on target detection accuracy.

Paper Details

Date Published: 6 November 1996
PDF: 16 pages
Proc. SPIE 2821, Hyperspectral Remote Sensing and Applications, (6 November 1996); doi: 10.1117/12.257172
Show Author Affiliations
Mark S. Schmalz, Univ. of Florida (United States)
Frank M. Caimi, Harbor Branch Oceanographic Institution, Inc. (United States)

Published in SPIE Proceedings Vol. 2821:
Hyperspectral Remote Sensing and Applications
Sylvia S. Shen, Editor(s)

© SPIE. Terms of Use
Back to Top