Neuro-fuzzy logic application for hyperspectral remote sensing

Vincent Michael Contarino; Pavlo A. Molchanov; Yulia Y. Podobna; Iryna M. Petrosyuk

doi:10.1117/12.577955

20 January 2005 Neuro-fuzzy logic application for hyperspectral remote sensing

Vincent Michael Contarino, Pavlo A. Molchanov, Yulia Y. Podobna, Iryna M. Petrosyuk

Proceedings Volume 5655, Multispectral and Hyperspectral Remote Sensing Instruments and Applications II; (2005) https://doi.org/10.1117/12.577955
Event: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2004, Honolulu, Hawai'i, United States

Abstract

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.

Citation Download Citation

Vincent Michael Contarino, Pavlo A. Molchanov, Yulia Y. Podobna, and Iryna M. Petrosyuk "Neuro-fuzzy logic application for hyperspectral remote sensing", Proc. SPIE 5655, Multispectral and Hyperspectral Remote Sensing Instruments and Applications II, (20 January 2005); https://doi.org/10.1117/12.577955

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