CQ100: a high-quality image dataset for color quantization research

Abstract

[EN]Color quantization ( CQ ) is a classical image processing operation that reduces the number of distinct colors in a given image. Although the idea of CQ dates back to the early 1970s, the first true CQ algorithm, median-cut, was proposed later in 1980. Since then, hundreds of publications have investigated the topic of CQ, proposing dozens of algorithms. A vast majority of these publications demonstrate their results on small datasets, containing a handful of images of mixed quality. Furthermore, the reproducibility of CQ research is often limited due to the use of private test images or public test images with multiple non-identical copies on the World Wide Web or restrictive licenses. To address these problems, we curated a large, diverse, and high-quality dataset of 24-bit color images called CQ 100 and released it under a permissive license. We present an overview of CQ 100 and demonstrate its use in comparing CQ algorithms.