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首页> 外文期刊>Journal of Imaging Science and Technology >Estimation of Chromatic Characteristics of Scene Illumination in an Image by Surface Recovery from the Highlight Region
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Estimation of Chromatic Characteristics of Scene Illumination in an Image by Surface Recovery from the Highlight Region

机译：通过高光区域的表面恢复估计图像中场景照明的色度特性

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摘要

This article proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source using its chromaticity determined based on the perceived illumination and highlight region. The proposed algorithm is composed of three steps. First, the illuminant chromaticity of the global incident light is estimated using a hybrid method that combines the perceived illumination and highlight region. Second, the surface spectral reflectance is then recovered from the image after decoupling the global incident illuminant for each channel. The surface spectral reflectance calculation is limited to the MAR (maximum achromatic region), which is the most achromatic and brightest region in the image, and estimated using the PCA (principal component analysis) method along with a set of given Munsell samples. Third, the closest colors are selected from a spectral database composed of reflected-lights generated by the given Munsell samples and a set of illuminants. Finally, the illuminant of the image is calculated using the average spectral distributions of the reflected-lights selected for the MAR region and its average surface reflectance. Experimental results confirmed the accuracy of the estimates produced by the proposed method for various illuminants.
机译：本文提出了一种光源估计算法，该算法使用入射光的色度来估计入射光源的光谱功率分布，该色度基于感知的照明度和高光区域确定。所提出的算法包括三个步骤。首先，使用混合方法估计全局入射光的发光色度，该混合方法将感知的照明和高光区域组合在一起。其次，在将每个通道的全局入射光源解耦之后，然后从图像中恢复表面光谱反射率。表面光谱反射率计算仅限于MAR（最大消色差区域），MAR是图像中最消色差和最亮的区域，并且使用PCA（主成分分析）方法以及一组给定的Munsell样本进行估算。第三，从光谱数据库中选择最接近的颜色，该光谱数据库由给定的孟塞尔样品产生的反射光和一组光源组成。最后，使用为MAR区域选择的反射光的平均光谱分布及其平均表面反射率来计算图像的光源。实验结果证实了所提出的方法对各种光源的估计结果的准确性。

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