Share Email Print

Proceedings Paper

Neural network to extract size parameter from light scattering data
Author(s): Patricia G. Hull; Mary S. Quinby-Hunt
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A computer-simulated neural network is described that successfully identifies the size parameter of particles in a sample of ocean water from its S34 Mueller matrix element. In the Mueller matrix formalism, the polarization states of the incident and scattered light are described by four- element Stokes vectors, and the effect of the scattering medium on the incident beam is described by the sixteen- element Mueller or scattering matrix. The experimental measurements of the Mueller matrix elements as functions of the scattering angle contain all the information on optical properties, size parameter, and shape of the particles that make up the scattering medium, although it is not a simple task to retrieve it. The pattern recognition and classification properties of an artificial neural network, such as that described here, offer a new and powerful approach to retrieving the information.

Paper Details

Date Published: 6 February 1997
PDF: 7 pages
Proc. SPIE 2963, Ocean Optics XIII, (6 February 1997); doi: 10.1117/12.266482
Show Author Affiliations
Patricia G. Hull, Tennessee State University (United States)
Mary S. Quinby-Hunt, Lawrence Berkeley Laboratory (United States)

Published in SPIE Proceedings Vol. 2963:
Ocean Optics XIII
Steven G. Ackleson; Robert J. Frouin, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?