Filter löschen
Filter löschen

how PCA can be applied to an image to reduce its dimensionality with example?

77 Ansichten (letzte 30 Tage)
Dimensionality reduction
  3 Kommentare
Image Analyst
Image Analyst am 14 Sep. 2021
@SHEETAL AGRAWAL, perhaps. You obviously need at least two features. What would be your two features? Maybe gray level is one, but what is the other? Or do you just have two different features, like blob area and blob texture or brightness?

Melden Sie sich an, um zu kommentieren.

Akzeptierte Antwort

Image Analyst
Image Analyst am 24 Dez. 2014
Bearbeitet: Image Analyst am 14 Apr. 2020
Here's code I got from Spandan, one of the developers of the Image Processing Toolbox at the Mathworks:
Here some quick code for getting principal components of a color image. This code uses the pca() function from the Statistics Toolbox which makes the code simpler.
I = double(imread('peppers.png'));
X = reshape(I,size(I,1)*size(I,2),3);
coeff = pca(X);
Itransformed = X*coeff;
Ipc1 = reshape(Itransformed(:,1),size(I,1),size(I,2));
Ipc2 = reshape(Itransformed(:,2),size(I,1),size(I,2));
Ipc3 = reshape(Itransformed(:,3),size(I,1),size(I,2));
figure, imshow(Ipc1,[]);
figure, imshow(Ipc2,[]);
figure, imshow(Ipc3,[]);
In case you don’t want to use pca(), the same computation can be done without the use of pca() with a few more steps using base MATLAB functions.
Hope this helps.
-Spandan
Also attached are some full demos.
  12 Kommentare
Ben Grassi
Ben Grassi am 13 Feb. 2020
Thanks so much for the help, getframe() gave me exactly what I needed.

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (7)

Devan Marçal
Devan Marçal am 13 Aug. 2015
Hi,
in your example you used PCA in just one image. I have an image bank a total of ~ 800 images. If I make a loop (if, while, etc ..) using the PCA function for each image individually, will be using this command wrong or inefficiently?
Thanks a lot.
Devan
  8 Kommentare
Darshan Jain
Darshan Jain am 25 Jul. 2019
Hey @ImageAnalyst,
I checked out your script, I had a small question, How could I plot the colored image back in three plots (showing approximation by pca1, then pca1 and pca2 and then followed by pca1, pca2 and pca3).
I tried doing using the imfuse comand "imfuse(pca1,pca2)", the clarity improved well, but i'm not able to reproduce the same colors. (see the attached image)
I think this is because I need to normalize the data, and then un-normalize it back before plotting. (I'm not sure though)
Image Analyst
Image Analyst am 25 Jul. 2019
Etworld, I just ran the colored chips image and it ran fine. Did you change my code at all?
00_Screenshot.png
Darshan: where did your colors come from? I don't understand what your "approximations" are supposed to be. But anyway, you can stitch images side by side if they are all RGB images to begin with:
wideImage = [rgbImage1, rgbImage2, rgbImage3];

Melden Sie sich an, um zu kommentieren.


Shaveta Arora
Shaveta Arora am 30 Jan. 2016
Can I have the pca code used in this color image example
  6 Kommentare
Shaveta Arora
Shaveta Arora am 31 Jan. 2016
Might possible. Pls share this pca function to save in my folder.
Image Analyst
Image Analyst am 31 Jan. 2016
I can't. It would not be legal. You either have to buy the toolbox from the Mathworks, or implement it yourself from low level code.

Melden Sie sich an, um zu kommentieren.


Anitha Anbazhagan
Anitha Anbazhagan am 17 Sep. 2016
I have 200 ROIs from each of the 50 images. For each ROI, I have 96 feature vectors for four different frequency bands. It seems very high dimensional. How to apply PCA for this? PCA should be applied to data matrix. Do I have to apply for each image or each ROI?
  1 Kommentar
Image Analyst
Image Analyst am 17 Sep. 2016
It depends on if you want PCA components on each image individually, or the PCA components of the group as a whole.

Melden Sie sich an, um zu kommentieren.


Mina Kh
Mina Kh am 11 Dez. 2016
Hi. I have multispectral( multi channel) data and I want to apply PCA to reduce the number of channel. Can u give me some hint?Which code i have to use?

Arathy Das
Arathy Das am 20 Dez. 2016
How can i extract three texture features among the 22 using PCA?
  1 Kommentar
Image Analyst
Image Analyst am 20 Dez. 2016
I think you should start your own discussion with your own data or images. If you have 22 PCA columns, then just extract the 3 you want as usual.
pca3 = pca22(:, 1:3); % or whatever.

Melden Sie sich an, um zu kommentieren.


joynjo
joynjo am 24 Mär. 2018
How to visualize the result of PCA image in pseudocolor?

F M Anim Hossain
F M Anim Hossain am 6 Apr. 2018
I'm new to the concept of PCA. I'm trying to develop something that can recognize color features from different images. Is it possible to do it with the help of PCA?

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by