Application of the K-Means Algorithm in Image Compression
Keywords:
K-Means, Clustering, Image compressionAbstract
In the Internet era, image information is widely used across all industries. The volume of image data is enormous, so effective transmission and storage require image compression. The K-Means algorithm is one of the most commonly used clustering algorithms. This paper applies the clustering approach to image compression and uses Python to implement K-Means clustering for image compression. Experimental results show that K-Means clustering can indeed compress images.
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Copyright (c) 2025 Hongxia Mao
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
