Neural network to extract size parameter from light scattering data

Patricia G. Hull; Mary S. Quinby-Hunt

doi:10.1117/12.266482

6 February 1997 Neural network to extract size parameter from light scattering data

Patricia G. Hull, Mary S. Quinby-Hunt

Proceedings Volume 2963, Ocean Optics XIII; (1997) https://doi.org/10.1117/12.266482
Event: Ocean Optics XIII, 1996, Halifax, Nova Scotia, Canada

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.

Citation Download Citation

Patricia G. Hull and Mary S. Quinby-Hunt "Neural network to extract size parameter from light scattering data", Proc. SPIE 2963, Ocean Optics XIII, (6 February 1997); https://doi.org/10.1117/12.266482

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