Preprocessing remotely sensed data for efficient analysis and classification

Patrick M. Kelly; James M. White

doi:10.1117/12.141745

23 March 1993 Preprocessing remotely sensed data for efficient analysis and classification

Patrick M. Kelly, James M. White

Proceedings Volume 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry; (1993) https://doi.org/10.1117/12.141745
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Interpreting remotely sensed data typically requires expensive, specialized computing machinery capable of storing and manipulating large amounts of data quickly. In this paper, we present a method for accurately analyzing and categorizing remotely sensed data on much smaller, less expensive platforms. Data size is reduced in such a way as to retain the integrity of the original data, where the format of the resultant data set lends itself well to providing an efficient, interactive method of data classification.

Citation Download Citation

Patrick M. Kelly and James M. White "Preprocessing remotely sensed data for efficient analysis and classification", Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); https://doi.org/10.1117/12.141745

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