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About this paper
Muragul Muratbekova, Nuray Toganas, Ayan Igali, Maksat Shagyrov, Elnara Kadyrgali, Adilet Yerkin, Pakizar Shamoi
This study provides a comprehensive review and experimental comparison of various color models, quantitatively assessing their computational efficiency and intuitiveness for human interaction. It demonstrates that while HS* family models offer high intuitiveness and fast processing, perceptually uniform CIE models incur significant computational overhead.
Key insights
- A fundamental trade-off exists where perceptually uniform models (e.g., CIE Lab) are computationally expensive, while faster models (e.g., YIQ, HSL) often lack complete perceptual uniformity.
- The HS* family of models (HSI, HSV, HSL) demonstrated the highest intuitiveness for human manipulation and rapid computational performance.
- Research in color models has evolved, shifting from theoretical and measurement-focused studies (pre-2010) to application-driven approaches leveraging machine learning (post-2010).
Summary by alphaXiv.
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