• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>SPIE Conference on Color Imaging : Displaying, Processing, Hardcopy, and Applications >LabRGB : Evaluation of the weighting factors
【24h】

LabRGB : Evaluation of the weighting factors

机译：LabRGB：评估加权因子

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Spectral distribution can be written as a linear combination of eigenvectors and the eigenvectors method gives the least estimation error, but eigenvectors depend on a sample selection of population and encoding values have no physical meaning. Recently reported LabPQR [1] is to convey physical values, but still is dependent on a sample selection of population. Thus, LabRGB [2] was proposed in 2007. LabRGB is to provide "sample selection of population" free spectral encoding/decoding methods. LabRGB consists of six unique trigonometric base functions and physically meaningful encoding values. LabRGB was applied to the real multispectral images and showed almost equal performance to traditional orthogonal eigenvector method in spectral estimation, and even better performance in colorimetric estimation. In this paper, the weighting factors of the base functions were examined in terms of their possible ranges. The numerical values are obtained by using a linear programming technique, and the results are also confirmed by using the Monte Carlo method. The results indicate that the possible ranges of six scores for six base functions are well within -80 to 80. The ranges thus obtained give a good clue for explicitly defining the bit depths of respective scores for the future applications and standardization.
机译：可以将光谱分布写成特征向量的线性组合，并且特征向量方法提供最少的估计误差，但特征向量取决于种群的样本选择，编码值没有物理含义。最近报告的Labpqr [1]是传达物理值，但仍然依赖于样本选择人口。因此，LabRGB [2]是在2007年提出的。LabRGB是提供“种群样品选择”自由谱编码/解码方法。 LabRGB由六个独特的三角基础函数和物理上有意义的编码值组成。 LabRGB应用于真实的多光谱图像，并在光谱估计中向传统的正交特征向量方法显示出几乎相等的性能，以及比色度估计更好的性能。在本文中，根据可能的范围检查基本功能的加权因素。通过使用线性规划技术获得数值，并且还通过使用蒙特卡罗方法来确认结果。结果表明，六个基本函数的六种分数的可能范围在-80到80内。因此，所获得的范围为未来应用和标准化明确地定义各个分数的比特深度提供了良好的线索。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号