Scene classification and segmentation using multispectral sensor fusion implemented with neural networks

Laurence E. Lazofson; Thomas J. Kuzma

doi:10.1117/12.152527

2 September 1993 Scene classification and segmentation using multispectral sensor fusion implemented with neural networks

Laurence E. Lazofson; Thomas J. Kuzma

Author Affiliations +

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152527
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Near-simultaneous, multispectral, coregistered imagery of ground target and background signatures were collected over a full diurnal cycle in the MWIR, LWIR, near-infrared, blue, green, and red wavebands using Battelle's portable sensor suite. The imagery data were processed with classical statistical algorithms and artificial neural networks to discriminate target signatures from background clutter and investigate automatic target detection and recognition schemes.

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Laurence E. Lazofson, Laurence E. Lazofson, Thomas J. Kuzma, Thomas J. Kuzma, } "Scene classification and segmentation using multispectral sensor fusion implemented with neural networks", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152527; https://doi.org/10.1117/12.152527

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