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Re: Singular Value Decomposition in 3 Dimensions [message #62368 is a reply to message #62289]

Wed, 03 September 2008 04:46

Mort Canty
Messages: 134
Registered: March 2003

Senior Member

tomandwilltamu08@gmail.com schrieb:
> I am wondering how to do Singular Value Decomposition in 3 Dimensions
> in IDL. All of the canned routines seem to work only on 2D arrays.
>
> Specifically, I am trying to preform Principle Component Analysis on
> stacks of 2D images.
>
> For example, how can one preform an SVD on a 2048x2048xn array to get
> 2048x2048 principle components?
>
> Thanks much,
> -Will

SVD is a decomposition theorem for matrices (2D arrays). I think you may
have an incorrect understanding of what principal (not principle)
component analysis means. If you apply PCA to a stack of n 2048x2048
images, you will get n 2048x2048 principal component images. The n
images will be uncorrelated and stacked in the order of decreasing
variance.

Mort

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[Message index]

		Singular Value Decomposition in 3 Dimensions By: tomandwilltamu08 on Tue, 02 September 2008 09:33
		Re: Singular Value Decomposition in 3 Dimensions By: Juggernaut on Wed, 03 September 2008 04:56
		Re: Singular Value Decomposition in 3 Dimensions By: Mort Canty on Wed, 03 September 2008 04:46
		Re: Singular Value Decomposition in 3 Dimensions By: Juggernaut on Wed, 03 September 2008 04:52

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