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I'm using ERDAS for my UAV image classification (consists 6 land cover types) and I performed the first step of Object-oriented classification, Single Feature Probability (SFP). It outputted a probability layer with value ranged from 0 to 1 indicating the similarity of every pixel to the training set.

However, it did not tell me the formula of how they calculated the SFP.

Could anyone give me a clue of it?

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As far as I know, SFP is the class probability derived from a Bayesian Network, i.e. a statistical supervised classifier that can incorporate both continuous and discrete information. There is a hint on that in this paper.

  • Thanks radouxju. I have also came to the same article as well. – Gloria Jan 14 '17 at 15:02

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