The Maximum Likelihood Estimation of Signature Transformation /MLEST/ algorithmThe Maximum Likelihood Estimation of Signature Transformation (MLEST) algorithm is used to obtain maximum likelihood estimates (MLE) of affine transformation. The algorithm has been evaluated for three sets of data: simulated (training and recognition segment pairs), consecutive-day (data gathered from Landsat images), and geographical-extension (large-area crop inventory experiment) data sets. For each set, MLEST signature extension runs were made to determine MLE values and the affine-transformed training segment signatures were used to classify the recognition segments. The classification results were used to estimate wheat proportions at 0 and 1% threshold values.
Document ID
19780056253
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Thadani, S. G. (Lockheed Electronics Co., Inc. Houston, Tex., United States)
Date Acquired
August 9, 2013
Publication Date
January 1, 1977
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Annual Symposium on Machine Processing of Remotely Sensed Data