A computationally-efficient maximum-likelihood classifier employing prior probabilities for remotely-sensed data
- 1 February 1985
- journal article
- research article
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 6 (2) , 369-376
- https://doi.org/10.1080/01431168508948456
Abstract
A time-efficient method for evaluating the maximum-likelihood classifier for LANDSAT MSS data is described and its extension to the case of unequal prior probabilities is summarized, following Shlien (1975) and Strahler (1980). The use of unequal prior probabilities is demonstrated by example and it is shown that, where classes are well-separated, then the effect of including prior probability estimates is negligible, but where classes are closely-related, then the choice of prior probability estimate can have a considerable effect.Keywords
This publication has 1 reference indexed in Scilit:
- The use of prior probabilities in maximum likelihood classification of remotely sensed dataRemote Sensing of Environment, 1980