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Separating a color signal into illumination and surface reflectance components: theory and applications

机译:将颜色信号分为照明和表面反射率分量:理论和应用

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A separation algorithm for achieving color constancy and theorems concerning its accuracy are presented. The algorithm requires extra information, over and above the usual three values mapping human cone responses, from the optical system. However, with this additional information-specifically, a sampling across the visible range of the reflected, color-signal spectrum impinging on the optical sensor-the authors are able to separate the illumination spectrum from the surface reflectance spectrum contained in the color-signal spectrum which is, of course, the product of these two spectra. At the heart of the separation algorithm is a general statistical method for finding the best illumination and reflectance spectra, within a space represented by finite-dimensional linear models of statistically typical spectra, whose product closely corresponds to the spectrum of the actual color signal. Using this method, the authors are able to increase the dimensionality of the finite-dimensional linear model for surfaces to a realistic value. One method of generating the spectral samples required for the separation algorithm is to use the chromatic aberration effects of a lens. An example of this is given. The accuracy achieved in a large range of tests is detailed, and it is shown that agreement with actual surface reflectance is excellent.
机译:提出了一种用于实现颜色恒定性的定理算法及其有关精度的定理。该算法需要来自光学系统的除了映射人体锥体响应的通常三个值以外的其他信息。然而,有了这些额外的信息,特别是在可见光范围内,入射到光学传感器上的反射色信号光谱进行了采样-作者能够将照明光谱与色信号光谱中包含的表面反射光谱分开当然,这是这两个光谱的乘积。分离算法的核心是一种一般的统计方法,用于在统计典型光谱的有限维线性模型所表示的空间内找到最佳照明和反射光谱,该模型的乘积与实际彩色信号的光谱非常接近。使用此方法,作者可以将表面的有限维线性模型的维数增加到实际值。产生分离算法所需的光谱样本的一种方法是使用透镜的色差效应。举一个例子。详细介绍了在各种测试中获得的精度,并且表明与实际表面反射率的一致性非常好。

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