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Image compression is a key component in the transmission and storage process of image data. The major objective of image compression is to reduce the irrelevance and redundancy of the image data in order to store and transmit them in an efficient form. One of the practical approaches is to reduce the original large color space to a considerable small scale. In detail, we implement this image compression method via two approaches: K-means, which directly clustering the colors to nearest centroids, and the SLIC superpixel approaches, which relies on generating computationally efficient and perceptually meaningful image segments. Experiment results reveal that both of our approaches could effectively compress the image size.

Image compression via K-means and SLIC superpixel approaches