This note presents an airborne spectral imaging system and methodology used to detect, track and monitor marine
mammal populations. The system is a four band multispectral imaging system using spectral bands tailored for maritime
imaging. This low cost, low volume, imaging sensor can be deployed on either a small unmanned air vehicle (UAV) or
any other cost efficient aircraft. Results of recent multispectral data collects over marine mammals in St. Lawrence
Seaway are presented. Species present included beluga whales as well as various species of larger baleen whales.
Narrow band polarization measurements were taken from a bridge in San Diego Harbor using the Advanced Coherent
Technologies Multi-mission Adaptable Narrowband Imaging Spectrometer (MANTIS) multichannel imaging system.
MANTIS was capable of simultaneously collecting four channels of imagery through a narrowband green (532 nm) filter
together with linear polarizers oriented at 0, 45, 90, and 135 degrees. This configuration enabled the collection of the
first three Stokes Vector elements. The data is being gathered to explore methods of calculating the sea surface Mueller
Matrix. Models, methods, and measurements are presented. Of specific interest is the deviation of the modeled data
from the measured data and its causes. The data and a model are used to estimate the contribution of upwelled polarized
light.
New approach to high-speed detection and modulation based on application of capacitance modulation is offered. Application of capacitance modulation allows to increase sensitivity and noise immunity of high-speed photodetectors in microwave range.
The original approach for the optical information processing for the hyperspectral remote sensing systems is developed on the union basis of the two mathematical tools: fuzzy logic and neural network. The optical information processing includes the complicated calculations and final results can give a large error. It is well known that there are large number of input parameters and some there uncertainty in the case of information processing of hyperspectral remote sensing systems. The using of statistical and determined models give the result having quite a large error of optical information processing and the given calculations take a lot of time to compute. Therefore the neoro-fuzzy logic application can be more expediency for processing of opto-electronic signals.
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