Principal Component Analysis (PCA) on images in MATLAB (GUI)

Version 1.0.5 (12.2 MB) by ABHILASH SINGH
Principal Component Analysis (PCA) on images in MATLAB (GUI)
5.0
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1.4K Downloads
Updated 17 Jan 2020
View License on GitHub
First, upload a colour image by clicking on the “upload an image button”. The acceptable image formats are png, jpg, jpeg, img and tif. Then click on the "Plot the grayscale image". After that enter the no. of PC's up to which you want to retrieve the images (both colour and grayscale).
An error message/box will pop-up when you enter a number greater than the no. of PCs for that particular image. Also, an error will message will pop-up when the entered input is not a number.
Please go through this link for detail explanation;
https://medium.com/@abhilash.singh/principal-component-analysis-pca-on-images-in-matlab-a-graphical-user-interface-gui-3d4999ddd0d0
For a detail understanding of PCA, please refer my lecture on PCA;
https://www.youtube.com/watch?v=ZLpQ6cbHxmY
Enjoy!!!

Cite As

ABHILASH SINGH (2026). Principal Component Analysis (PCA) on images in MATLAB (GUI) (https://github.com/abhilash12iec002/Principal-Component-Analysis-PCA-on-images-in-MATLAB-GUI-), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Dimensionality Reduction and Feature Extraction in Help Center and MATLAB Answers
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Version Published Release Notes
1.0.5

Added video link.
1.0.4

Link update
1.0.3

https://medium.com/@abhilash.singh/principal-component-analysis-pca-on-images-in-matlab-a-graphical-user-interface-gui-3d4999ddd0d0
1.0.2

GitHub upload
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.