PCA on a 3d Matrix

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Micheal Dennington
Micheal Dennington on 20 Jun 2020
Commented: Sanchay Mukherjee on 31 Jan 2022
Hi. I have a data set of http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes Indian Pines. Data set is a 145x145x200 matrix that 145x145 represents spatial dimensions, 200 represents feature dimensions. I wnat to do PCA dimension reduction but I can't figure out how to deal 3d matrix. If you could help me I would be appreciated. Thanks.
  3 Comments
Sanchay Mukherjee
Sanchay Mukherjee on 31 Jan 2022
Hi Michael,
Did you figure out hte solution? I am trying to do a similar thing. I have a matrix of 200*500*3, where 200*500 is the data for corresponding 3 features.

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Answers (1)

Subhadeep Koley
Subhadeep Koley on 16 Nov 2020
You can use the hyperpca function to achieve the same.
% Definenumber of principal components you require
numComponents = 10;
% Perform PCA transform
outputDataCube = hyperpca(indianPinesMatrix, numComponents);
The above mentioned feture comes under Image Processing Toolbox's Hyperspectral Imaging Library support package, and can be downloaded from here. For more information on Hyperspectral Imaging Library see the documentation.

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