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

Principal Component Analysis (PCA) on images in MATLAB (GUI)
1.3K descargas
Actualizado 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!!!

Citar como

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. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2019b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Categorías
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Versión Publicado Notas de la versión
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

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.