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使用最佳训练组对宽色域摄像机进行色彩转换

Yasheng Li¹, Ningfang Liao¹, Yumei Li¹

¹State Key Discipline Laboratory of Color Science and Engineering, School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China.

Sensors (Basel, Switzerland)

|August 26, 2023

概括

建立准确的色彩转换模型用于宽色域相机是具有挑战性的. 这项研究使用了与皮尔森相关性的最佳方法来提高RGB到XYZ转换精度,以获得更好的显示色彩再现.

科学领域:

颜色科学颜色科学
计算机视觉计算机视觉
显示技术显示技术

背景情况:

准确的色度转换对于宽色域 (WCG) 显示器至关重要.
为WCG摄像机建立精确的转换模型存在重大挑战.
现有的方法很难在整个色彩空间中实现所需的近似精度.

研究的目的:

提出一种最优的方法来建立从相机RGB到CIEXYZ空间的颜色转换模型.
为了提高广泛的颜色范围应用的颜色转换的准确性.
研究改善色彩转换模型性能的方法.

主要方法:

使用皮尔森相关系数来评估RGB和XYZ值之间的线性相关性.
根据高线性相关性选择最佳的训练数据组.
开发和测试颜色转换模型,包括多项式变换和BP人工神经网络 (BP-ANN).
在CIE1976L*a*b*空间中,分析用色彩角度和色彩划分的样本组.

主要成果:

建议的最佳方法有效地识别出具有优异线性相关性的训练组.
与最佳选择的组进行训练的颜色转换模型表现出更高的准确性.
实验结果显示,在使用色调-角度-分割训练组进行多项式变换时,颜色转换误差减少 (CIE1976L*a*b*颜色差异).
BP-ANN模型也显示了性能,但以色调为基础的聚项变换特别有效.

结论:

使用皮尔森相关性的最佳方法显著提高了WCG摄像头RGB到XYZ色彩转换模型的准确性.
将训练数据按色调角度划分提高了基于多项式的色彩转换模型的效率和准确性.
这些发现有助于在宽色域显示系统中更准确的色彩再现.

关键词:

颜色转换颜色转换颜色转换颜色测量表征的色度表征.数字摄像头是数字摄像机.多项式变换的多项式变换

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