Likelihood-based Image Segmentation and Classification : Concepts and Applications

Abstract

This paper describes a likelihood-based segmentation and classification method for remotely sensed images. It is based on optimization of a utility function, described as a function of likelihood of all objects and their parameters. As the likelihood or posterior probabilities are calculated per object rather than per pixel, the variance in (spectral… (More)

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