Optimum sensors for color constancy in scenes illuminated by daylight.
Optimum sensors for color constancy in scenes illuminated by daylight.
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DOI：
10.1364/josaa.27.002198
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
Sivalogeswaran Ratnasingam;S. Collins;J. Hernández-Andrés
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文献类型：
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作者：
Sivalogeswaran Ratnasingam;S. Collins;J. Hernández-Andrés
场景中物体的外观颜色取决于照亮物体的光的光谱。然而，在许多机器视觉应用中，独立于光源光谱记录物体的颜色是重要的。在本文中，基于黑体模型的颜色恒常性算法，需要四个传感器具有不同的光谱响应的性能进行了研究，在日光照明。在这项调查中，传感器噪声被建模为高斯噪声，并使用不同的比特数的响应进行量化。研究了一种基于投影的算法，其输出对光照不变性，以改善所获得的结果。这两种算法的性能，然后通过优化的光谱灵敏度的四个传感器使用免费提供的CIE标准日光光谱和一组亮度归一化孟塞尔反射率数据。与优化的传感器，这两种算法的性能被证明是人类视觉系统相媲美。然而，用测量的日光光谱获得的结果表明，标准日光可能不足以代表用于用标准日光优化的测量的日光，以产生一组可靠的最佳传感器特性。
The apparent color of an object within a scene depends on the spectrum of the light illuminating the object. However, recording an object's color independent of the illuminant spectrum is important in many machine vision applications. In this paper the performance of a blackbody-model-based color constancy algorithm that requires four sensors with different spectral responses is investigated under daylight illumination. In this investigation sensor noise was modeled as gaussian noise, and the responses were quantized using different numbers of bits. A projection-based algorithm whose output is invariant to illuminant is investigated to improve the results that are obtained. The performance of both of these algorithms is then improved by optimizing the spectral sensitivities of the four sensors using freely available CIE standard daylight spectra and a set of lightness-normalized Munsell reflectance data. With the optimized sensors the performance of both algorithms is shown to be comparable to the human visual system. However, results obtained with measured daylight spectra show that the standard daylights may not be sufficiently representative of measured daylight for optimization with the standard daylight to lead to a reliable set of optimum sensor characteristics.