| Re: Maximum likelihood question (ENVI) [message #37596 is a reply to message #37579] |
Thu, 08 January 2004 11:04   |
Jonathan Greenberg
Messages: 91
Registered: November 2002
|
Member |
|
|
Mort:
Did RSI send you ANYTHING? Could you post them to the newsgroup? Also,
is there a program to do the Richard's method, or did you code it directly
from a publication? Thanks!
--j
On 1/8/04 7:48 AM, in article btju5i$cm0j$1@zam602.zam.kfa-juelich.de, "Mort
Canty" <m.canty@fz-juelich.de> wrote:
> Hi Jonathan,
>
> I posted the self-same question to this newsgroup shortly after ENVI 3.6
> appeared and after not having received a satifactory answer from RSI.
> Unfortunately it got no takers here. Maybe someone will take pity now that
> there are two of us.
>
> Cheers
>
> Mort Canty
>
> PS I use the probability vectors for Richards' post-calssification
> "Probabilistic Label Relaxation" method.
>
> "Jonathan Greenberg" <greenberg@ucdavis.edu> schrieb im Newsbeitrag
> news:gC4Lb.7043$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.
>>
>>
>>
>
>
|
|
|
|
comp.lang.idl-pvwave archive
Members
Search
Help
Login
Home
