CQ100: A High-Quality Image Dataset for Color Quantization Research

Published: 17 December 2024| Version 4 | DOI: 10.17632/vw5ys9hfxw.4
Contributors:
M. Emre Celebi,

Description

CQ100 is a diverse and high-quality dataset of color images that can be used to develop, test, and compare color quantization algorithms. The dataset can also be used in other color image processing tasks, including filtering and segmentation. If you find CQ100 useful, please cite the following publication: M. E. Celebi and M. L. Perez-Delgado, “CQ100: A High-Quality Image Dataset for Color Quantization Research,” Journal of Electronic Imaging, vol. 32, no. 3, 033019, 2023. You may download the above publication free of charge from: https://www.spiedigitallibrary.org/journals/journal-of-electronic-imaging/volume-32/issue-3/033019/cq100--a-high-quality-image-dataset-for-color-quantization/10.1117/1.JEI.32.3.033019.full?SSO=1

Files

Steps to reproduce

Collected from the WWW (Wikimedia Commons, PxHere, and Kodak Lossless True Color Image Suite)

Institutions

University of Central Arkansas, Universidad de Salamanca

Categories

Artificial Intelligence, Computer Vision, Image Processing, Machine Learning, Clustering, Vector Quantization

Funding

Arkansas NSF EPSCoR

OIA-1946391

Licence