| Re: Maximum likelihood question (ENVI) [message #37602 is a reply to message #37596] |
Thu, 08 January 2004 07:48  |
Mort Canty
Messages: 134
Registered: March 2003
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Senior Member |
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Hi Jonathan,
I posted the self-same question to this newsgroup shortly after ENVI 3.6
appeared and after not having received a satifactory answer from RSI.
Unfortunately it got no takers here. Maybe someone will take pity now that
there are two of us.
Cheers
Mort Canty
PS I use the probability vectors for Richards' post-calssification
"Probabilistic Label Relaxation" method.
"Jonathan Greenberg" <greenberg@ucdavis.edu> schrieb im Newsbeitrag
news:gC4Lb.7043$ux1.4730@newssvr27.news.prodigy.com...
> I'm trying to generate images of true probabilities from maximum
likelihood
> rule images. Since the final probability rule images were modified (from
the
> RSI website): "In the ENVI 3.6 implementation, the rule images (one per
> class) contain a maximum likelihood discriminant function with a modified
> Chi Squared probability distribution.", I am unclear as to how to get BACK
> to true probabilities. Typing in the % probability into the rule
classifier
> doesn't really get me what I need. Could I get the "true" probability for
a
> given class (let's say we have two classes, A and B) and calculating:
>
> Rule image A/(rule image A + rule image B) ?
>
> Or is there some other technique I need to perform to get a true
probability
> image? Thanks!
>
> I'm planning on using this in combination with Bayesian logic tools, which
> is why I need, for each pixel and for each class the posterior probability
> (0 to 1). As I mentioned, the rule classifier is only good if I want to
> perform a new classification based on the rule images, not if I want to
see
> directly what these probabilities are.
>
>
>
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