A general non-parametric classifier applied to discriminating surface water from terrain shadowsA general non-parametric classifier is described in the context of discriminating surface water from terrain shadows. In addition to using non-parametric statistics, this classifier permits the use of a cost matrix to assign different penalties to various types of misclassifications. The approach also differs from conventional classifiers in that it applies the maximum-likelihood criterion to overall class probabilities as opposed to the standard practice of choosing the most likely individual subclass. The classifier performance is evaluated using two different effectiveness measures for a specific set of ERTS data.
Document ID
19760035950
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Eppler, W. G. (Lockheed Electronics Co., Inc. Aerospace Systems Div., Houston, Tex., United States)
Date Acquired
August 8, 2013
Publication Date
January 1, 1975
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Symposium on Machine Processing of Remotely Sensed Data