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Proceedings Paper

Informational properties of the masking atmospheric-optical channel over a remotely sensed onground objects
Author(s): Galib Ali Huseynov
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Paper Abstract

Simulation and calculation schemes for research informational characteristics of masking atmospheric-optical channel over a remotely sensed on-ground objects is problem considered in this work. Self-descriptiveness criteria is presented for informational models of masking remotely measured spectral-optical characteristics by transformation in an atmosphere. The self-descriptiveness of these models in inverse problems of the remotely sensed data with their optimum parameterization expressed in terms of bit/parameter is similar to a self descriptiveness of optical images in problems of recognition and expressed in terms bit/attributes. Differently, calculating a self-descriptiveness even for these two different types of problems (models' parameterization and pattern recognition), we have an opportunity to compare a remotely sensed data by means of the uniform metrics. From considered positions carrying out transformations to the information metrics of various distributions of spectral-optical and spatially-contrast characteristics of on-ground objects to be distinguished against backgrounds of natural objects image (soil-vegetative, wood and water), transformed by an atmosphere have to be effective. Relation of searching procedure for effective algorithms of an estimation the information maintenance of remotely sensed objects' parameters data with reception of the adequate metrics for remote data interpretation and with optimum parameterization of the atmospheric-optical masking channel is shown. Characteristic ranges of an optimum self-descriptiveness of aerosol masking transformation of optical characteristics are determined. Angular distributions transformation for deriving unmasking optical images are Illustrated. Accordingly, measurements' digitization as a result of planning and searching of optimum informative corners for unmasking with a choice optimum number of measurements and models' parameters are demonstrated.

Paper Details

Date Published:
PDF: 10 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661W; doi: 10.1117/12.777899
Show Author Affiliations
Galib Ali Huseynov, International Eco-Energy Academy (Azerbaijan)


Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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