Application of K-Means Algorithm in Image Compression - Mao, Hongxia (Journal of Artificial Intelligence and Information, 2025)
In the Internet era, image information is widely used in all walks of life. The amount of data in images is very large, and it is necessary to compress images in order to effectively transmit and store them. The K-Means algorithm is one of the most commonly used clustering algorithms. This article applies the clustering algorithm to image compression applications and uses the K-Means clustering algorithm to compress images through Python programming. From the experimental results, it can be concluded that the K-Means clustering method can indeed compress images.