基于向量夹角样本选择的光谱反射率重建

目的研究一种更有效的训练样本选择方法,以提高光谱反射率的重建精度。方法提出将样本看做向量,根据测试样本与训练样本之间的夹角判断两者间的相似度,然后把该夹角大小作为相似度权重赋予该训练样本,实验以孟塞尔色卡为样本集,训练样本分别为经过Mohammadi方法选择的样本和经过文中提出的向量夹角方法选择的样本,以色差和光谱均方根误差为评价指标,从重构精度和样本选择的有效性等2个方面对2种样本筛选方法进行比较和验证。结果通过Matlab软件仿真实验,文中所提方法的平均色差能降低到0.7945,最大色差为2.1569,平均光谱均方根误差降低到0.011 42,最大光谱均方根误差为0.0218。结论基于向量夹角选择样本具有简单且精确的优势,能够满足高精度颜色复制的要求,可以为快速准确地选择样本和提高颜色复制精度提供参考。

Spectral Reflectance Reconstruction Based on Vector Angle Sample Selection

The work aims to study a more effective training sample selection method to improve the reconstruction accuracy of spectral reflectance. The sample was proposed to be regarded as a vector, and the similarity between the test sample and the training sample was determined according to the angle between them. Then, the included angle was used as the similarity weight of the training sample. The experiment used the Munsell color card as a sample set, and the training samples were selected by Mohammadi method and the proposed method. With color difference and spectral root mean square error as the evaluation indexes, the two sample selection methods were compared and verified from two aspects: reconstruction accuracy and the effectiveness of sample selection. Through the Matlab software simulation experiment, the average color difference of the proposed method could be reduced to 0.7945, the maximum color difference was 2.1569, the mean spectral root mean square error was reduced to 0.011 42, and the maximum spectral root mean square error was 0.0218. The sample selection based on vector angle is simple and accurate, which can meet the requirements of high precision color reproduction and provide a reference for how to select samples quickly and accurately and improve the accuracy of color reproduction.