Image compression via K-means and SLIC superpixel approaches
- 10.2991/icmmita-16.2016.185How to use a DOI?
- Image Compression; K-means; Superpixel
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.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaolin Luo PY - 2017/01 DA - 2017/01 TI - Image compression via K-means and SLIC superpixel approaches BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 1008 EP - 1012 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.185 DO - 10.2991/icmmita-16.2016.185 ID - Luo2017/01 ER -