K Means Algorithm with the application to image compression

Version 1.0.0.0 (1,2 Mo) par Jason Rebello
This program uses the K means clustering algorithm to group the pixels in an image
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Mise à jour 25 juil. 2013

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- K means algorithm is performed with different initial centroids in order to get the best clustering.
- The total cost is calculated by summing the distance of each point to its cluster centre and then summing over all the clusters.
- Based on the minimum overall cost achieved during each iteration of 'iterKMeans' the pixel assignment to their respective clusters are made and final compressed image is obtained.
- This algorithm will run slower as the number of clusters , size of the image and number of iterations increase.

Citation pour cette source

Jason Rebello (2024). K Means Algorithm with the application to image compression (https://www.mathworks.com/matlabcentral/fileexchange/42829-k-means-algorithm-with-the-application-to-image-compression), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2012a
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K Means/

Version Publié le Notes de version
1.0.0.0