Hi Jordi,

Thank you for your answer and the wiki link! I read carefully the wiki 
section, and this is all fine, but I do not know how to interpret the 
output image of the “otbcli_DimensionalityReduction”.  


Is the output image the pca-transformed input image? If yes, why is the 
standard deviation of each band in the output image equal to 1?


You also mentioned the following “You can use the eigenvalues … They are 
stored in a file 
which has the same name as the model but with a .txt extension. ”.


Maybe I am missing something here, but in “otbcli_DimensionalityReduction” 
there is no “model” parameter. The only txt file I can get is a 9x9 matrix 
resulting from the option “-outmatrix”. However, in the otb help, it is 
explained shortly that this is a “transformation matrix”. 


Does the “-outmatrix” option provide a matrix with the eigenvectors? 


Thank you for your time and help!

Cheers,

Kimi    

On Monday, 3 September 2018 11:46:43 UTC+2, jordi.inglada wrote:
>
> Hi Kimi, 
>
> The components are given as directions (eigenvectors) and are therefore 
> normalized (unit vectors). You can use the eigenvalues (the variance of 
> each direction) to select the components[1]. They are stored in a file 
> which has the same name as the model but with a .txt extension. 
>
> Best wishes, 
>
> Jordi 
>
> [1]  https://en.wikipedia.org/wiki/Principal_component_analysis#Intuition 
>

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