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大色域激光显示设备的亮度预测

Brightness Prediction of Large Color Gamut Laser Display Devices.

作者信息

Zhu Jianying, Gao Weinan, Bi Yong, Xu Zuyan, Sun Minyuan

机构信息

Applied Laser Research Center, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Micromachines (Basel). 2023 Sep 27;14(10):1850. doi: 10.3390/mi14101850.

DOI:10.3390/mi14101850
PMID:37893288
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10609144/
Abstract

A brightness-perceived color appearance model tailored for large gamut display devices, exemplified by laser displays, was investigated. Psychophysical experiments on the brightness matching of 30 color stimuli with achromatic white light were conducted by 16 observers. The analysis compares the performance of a number of existing color appearance models and equivalent luminance models in predicting brightness. None of the models performed acceptably due to a severe underestimation of the Helmholtz-Kohlrausch (H-K) effect. A modified model of perceived brightness based on CAM16, taking into account the H-K effect, is proposed. Evaluated by psychophysical experiments, the proposed model exhibits a superior performance compared to the preceding models, especially within the extensive color gamut range stipulated by BT.2020. The results help to optimize the design of laser displays with a wide color gamut and high perceived brightness.

摘要

研究了一种针对大色域显示设备(以激光显示器为例)量身定制的亮度感知颜色外观模型。16名观察者对30种颜色刺激与消色差白光进行了亮度匹配的心理物理实验。该分析比较了许多现有颜色外观模型和等效亮度模型在预测亮度方面的性能。由于对亥姆霍兹-科尔劳施(H-K)效应严重低估,没有一个模型的表现令人满意。提出了一种基于CAM16并考虑H-K效应的感知亮度修正模型。通过心理物理实验评估,所提出的模型与先前模型相比表现出卓越的性能,尤其是在BT.2020规定的广泛色域范围内。这些结果有助于优化具有宽色域和高感知亮度的激光显示器的设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/641c49a3c92d/micromachines-14-01850-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/7be1bfea4f7d/micromachines-14-01850-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/f45ccf99224e/micromachines-14-01850-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/20d981d77373/micromachines-14-01850-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/7aeb45537327/micromachines-14-01850-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/e50c55e34554/micromachines-14-01850-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/f15ccb67431f/micromachines-14-01850-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/9be47703e3ff/micromachines-14-01850-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/33d1b7935ad7/micromachines-14-01850-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/641c49a3c92d/micromachines-14-01850-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/7be1bfea4f7d/micromachines-14-01850-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/f45ccf99224e/micromachines-14-01850-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/20d981d77373/micromachines-14-01850-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/7aeb45537327/micromachines-14-01850-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/e50c55e34554/micromachines-14-01850-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/f15ccb67431f/micromachines-14-01850-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/9be47703e3ff/micromachines-14-01850-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/33d1b7935ad7/micromachines-14-01850-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67df/10609144/641c49a3c92d/micromachines-14-01850-g009.jpg

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