RT Journal Article
T1 An optimized, color-adaptive blue light filtering approach using a novel color space transformation
A1 Bayón Fernández, Juan
A1 Recas Piorno, Joaquín
A1 Guijarro Mata-García, María
AB Wearable screens are part of everyday life, but the blue light they emit can affect the human body. Known as the Blue Hazard, high-energy blue light has been linked to circadian rhythm disruption, reduced focus, cognitive functions, and Computer Vision Syndrome. As screens move closer to the eyes, especially in users with pre-existing eye conditions, effective filtering becomes increasingly important.This work presents a blue light filter that processes images in a novel color space, selectively reducing high-energy pixels while preserving most colors. After filtering, both contrast and image quality remain virtually unchanged, according to several widely used metrics.Physical measurements showed that blue light absorption exceeded theoretical expectations. Spectrophotometric tests across various screens demonstrated consistent performance—typically reducing 30%–40% of blue light for a color difference (ΔE) of 10, with absorption reaching up to 100%. Compared to f.lux and Night Shift, our filter reduces blue emissions by 17% and 34% more, respectively. With an average processing time of 0.012 s per image using basic parallelization (up to 85 Hz), it is well-suited for modern wearable and electronic devices.
PB Elsevier
YR 2025
FD 2025-07-07
LK https://hdl.handle.net/20.500.14352/122329
UL https://hdl.handle.net/20.500.14352/122329
LA eng
NO Bayón, J., Recas, J., & Guijarro, M. (2025). An optimized, color-adaptive blue light filtering approach using a novel color space transformation. Elsevier Displays 90, 103124 (2025). https://doi.org/10.1016/j.displa.2025.103124
NO Ministerio de Ciencia e Innovación
NO Cátedra de Tiflotecnología UCM ONCE
DS Docta Complutense
RD 10 jul 2025