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)
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!!!
Cite As
ABHILASH SINGH (2022). 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 LinuxCategories
Tags
Acknowledgements
Inspired by: Real Time Object Detection using Deep Learning.
Inspired: Principal Component Analysis (PCA) on LANDSAT-8 imagery , Linear Regression plot with Confidence Intervals in MATLAB, Verifying convolution theorem in image processing (2-D)
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To view or report issues in this GitHub add-on, visit the GitHub Repository.
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