K Means Algorithm with the application to image compression
- 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.
Citar como
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. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxCategorías
Etiquetas
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Descubra Live Editor
Cree scripts con código, salida y texto formateado en un documento ejecutable.
K Means/
Versión | Publicado | Notas de la versión | |
---|---|---|---|
1.0.0.0 |