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

版本 1.0.5 (12.2 MB) 作者: ABHILASH SINGH
Principal Component Analysis (PCA) on images in MATLAB (GUI)
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1.3K 次下载
更新时间 2020/1/17
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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!!!

引用格式

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. 检索时间: .

MATLAB 版本兼容性
创建方式 R2019b
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版本 已发布 发行说明
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

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。