Fast maximum likelihood classification of remotely-sensed imagery
- 1 May 1987
- journal article
- research article
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 8 (5) , 723-734
- https://doi.org/10.1080/01431168708948683
Abstract
We have devised, written and tested an implementation of the Gaussian Maximum Likelihood classification method for a commercial image processor. This has resulted in significant savings in execution time for the classification of multispectural remotely-sensed imagery, at very little cost to the accuracy, when compared to a software version of the same algorithm.Keywords
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