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

Principal Component Analysis (PCA) on images in MATLAB (GUI)
1,3K Downloads
Aktualisiert 17 Jan 2020
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;
For a detail understanding of PCA, please refer my lecture on PCA;
https://www.youtube.com/watch?v=ZLpQ6cbHxmY
Enjoy!!!

Zitieren als

ABHILASH SINGH (2024). Principal Component Analysis (PCA) on images in MATLAB (GUI) (https://github.com/abhilash12iec002/Principal-Component-Analysis-PCA-on-images-in-MATLAB-GUI-), GitHub. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2019b
Kompatibel mit allen Versionen
Plattform-Kompatibilität
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Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version Veröffentlicht Versionshinweise
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

1.0.1

Increases the no. of acceptable image format.

1.0.0

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.