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Journal of Applied Sciences
  Year: 2010 | Volume: 10 | Issue: 8 | Page No.: 636-643
DOI: 10.3923/jas.2010.636.643
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Classification of Remote Sensing Data with Markov Random Field

H. Fizazi Izabatene and R. Rabahi

The satellite observation with a resolution of ten meters provides images of earth surface. The precise spectral information allows a classification of earth objects. Due to some considerations, Markov Random Field has become a common search procedure. Attention has been focused on utilizing the spatial context in image classification; labels are to be assigned to individuals’ pixels or groups of pixels. In this approach, we relied on, among approaches to Markov Random Field to a supervised classification of satellite images. This approach is known as the Multi-Scales model. We use an energy expression according to Potts model.
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How to cite this article:

H. Fizazi Izabatene and R. Rabahi, 2010. Classification of Remote Sensing Data with Markov Random Field. Journal of Applied Sciences, 10: 636-643.

DOI: 10.3923/jas.2010.636.643






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