Preprocessing techniques to reduce atmospheric and sensor variability in multispectral scanner data.Multispectral scanner data are potentially useful in a variety of remote sensing applications. Large-area surveys of earth resources carried out by automated recognition processing of these data are particularly important. However, the practical realization of such surveys is limited by a variability in the scanner signals that results in improper recognition of the data. This paper discusses ways by which some of this variability can be removed from the data by preprocessing with resultant improvements in recognition results.
Document ID
19720028175
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Crane, R. B. (Michigan, University Ann Arbor, Mich., United States)
Date Acquired
August 6, 2013
Publication Date
January 1, 1971
Subject Category
Instrumentation And Photography
Meeting Information
Meeting: International Symposium on Remote Sensing of Environment, 7th, University of Michigan