中文摘要：

光谱反射率重建一般指采用标准色卡上的颜色样本,对成像系统进行光谱表征（Spectral character-ization）,进而从系统响应中精确地求出物体表面的光谱反射率。由于标准色卡的颜色样本数量较大,在实际成像系统中使用时有诸多不便。考虑到颜色样本之间存在较大冗余,可从中选出具代表性的少数样本用于光谱表征。针对已有方法未考虑实际成像系统特性的不足,文章提出了一种代表颜色的分步选取算法,即首先通过假设一个虚拟成像系统,根据全局误差最小的原则,挑选出部分最具代表性的颜色,估计出实际成像系统的光谱响应函数,然后在此基础上继续选择其余的代表颜色。实验表明,对于窄带多光谱成像系统及宽带彩色扫描仪而言,文章提出的方法在光谱精度及色度方面均明显优于先前方法。

英文摘要：

Spectral reflectance reconstruction, also referred to as spectral characterization, aims to recover accurate spectral reflectance of object surface by employing standard color charts. As there are always a large number of color samples on a color chart, spectral characterization becomes a time-consuming process for practical application. Some methods have been presented to selected representative color samples based on the redundancy of the colors on a chart. However, these methods only consider the distribution of spectral reflectance, and thus the selected colors may not be optimal for a specific imaging system. To deal with this problem, the present paper proposes a sequential method for the selection of most representative colors, which consists of two steps. In the first step, a part of representative colors are selected according to the minimization of mean spectral rootmean-square error, by assuming a virtual imaging system. The spectral responsivity of the real imaging system is then calculated based on these selected samples. In the second step, additional representative colors are selected based on the characteristics of the real imaging system. Two quite different systems, i. e. , an ll-channel narrowband multispectral imaging system and a 3- channel broadband color scanner, were used in the experiment. It was shown that the proposed method significantly outperforms the previous method in terms of both spectral and colorimetric accuracy.