Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data

Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data

The sizes of compressed images depend on their spatial resolution (number ofpixels) and on their color resolution (number of color quantization levels). Weintroduce DaltonQuant, a new color quantization technique for image compressionthat cloud services can apply to images destined for a specific…

arXiv.orgJose Cambronero

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Abstract

The sizes of compressed images depend on their spatial resolution (number of pixels) and on their color resolution (number of color quantization levels). We introduce DaltonQuant, a new color quantization technique for image compression that cloud services can apply to images destined for a specific user with known color vision deficiencies. DaltonQuant improves compression in a user-specific but reversible manner thereby improving a user's network bandwidth and data storage efficiency. DaltonQuant quantizes image data to account for user-specific color perception anomalies, using a new method for incremental color quantization based on a large corpus of color vision acuity data obtained from a popular mobile game. Servers that host images can revert DaltonQuant's image requantization and compression when those images must be transmitted to a different user, making the technique practical to deploy on a large scale. We evaluate DaltonQuant's compression performance on the Kodak PC reference image set and show that it improves compression by an additional 22%-29% over the state-of-the-art compressors TinyPNG and pngquant.

Cite as:

Cambronero, J., Stanley-Marbell, P., and Rinard, M. 2018. Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data. arXiv.org. https://arxiv.org/abs/1803.08420v1.

BibTeX:

@misc{cambronero2018incremental,
    title={Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data},
    author={Jose Cambronero and Phillip Stanley-Marbell and Martin Rinard},
    year={2018},
    eprint={1803.08420},
    archivePrefix={arXiv},
    primaryClass={cs.HC}
}