Computational Modeling For Smart Multispectral Sensor Design

F. O. Huck; R. E. Davis; S. K. Park; R. M. Aherron; R. F. Arduini

doi:10.1117/12.931930

6 November 1981 Computational Modeling For Smart Multispectral Sensor Design

F. O. Huck, R. E. Davis, S. K. Park, R. M. Aherron, R. F. Arduini

Proceedings Volume 0278, Electro-Optical Instrumentation for Resources Evaluation; (1981) https://doi.org/10.1117/12.931930
Event: 1981 Technical Symposium East, 1981, Washington, D.C., United States

Abstract

A computational model of the processes involved in multispectral remote sensing and data classification is being developed as a tool for designing smart sensors which can process, edit and classify the data that they acquire. By accounting for both stochastic and deter-ministic elements of solar radiation, atmospheric radiative transfer, surface and cloud reflectance, and sensor response, the model can be used to simulate and evaluate the performance of sensor spectral responses and concepts, data processing algorithms and topologies, and device performance characteristics for various tasks that might improve the efficiency of multispectral remote sensing. Typical tasks are editing of cloud cover and opaque haze, automatically correcting for atmospheric effects, and adaptively classifying data into land use categories and surface substances. Preliminary computational results are presented which illustrate the dependence of editing and classification errors on the selection of sensor spectral channels and data processing algorithms and topologies as well as on the natural variability of the atmospheric transmittance and surface reflectance. The results include an evaluation of the performance of three sets of spectral channels: the four Landsat D MSS and TM channels which are located in the visual and near-IR region, and the three channels which were proposed by Kondratyev et al for the survey of natural formations.

Citation Download Citation

F. O. Huck, R. E. Davis, S. K. Park, R. M. Aherron, and R. F. Arduini "Computational Modeling For Smart Multispectral Sensor Design", Proc. SPIE 0278, Electro-Optical Instrumentation for Resources Evaluation, (6 November 1981); https://doi.org/10.1117/12.931930

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