K Means Algorithm with the application to image compression

This program uses the K means clustering algorithm to group the pixels in an image
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Aggiornato 25 lug 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.

Cita come

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. Recuperato .

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Creato con R2012a
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Versione Pubblicato Note della release
1.0.0.0