针对彩色扫描仪的特点,采用主元分析法(PCA)和反向传播(BP)人工神经网络(ANN)相结合的方法对图像光谱重构进行研究。选择IT8.7/2标准色卡作为训练样本,将该色卡中的另一组色靶作为检验样本以讨论不同网络结构以及不同主元数和训练样本数对光谱重构的影响,再以自然色系统(NCS)色卡为检验样本来分析不同种类的训练和检验样本与光谱重构性能的关系。实验结果表明,采用3-14-6网络结构和6个主元数是最佳选择,训练样本和扫描目标之间的一致性是基于彩色扫描仪图像光谱重构的关键所在。

Based on the characteristics of the color scanner, the spectral reconstruction of images was studied using the method combining the principal component analysis (PCA) and back-propagation (BP) artificial neural network. The IT8.7/2 standard color card was adopted as the training samples, and the different set of patches in this card was used as testing samples to discuss the effect of different structure networks, principal component numbers and training sample numbers on the spectral reconstruction; meanwhile the color patches of Natural Color System (NCS) were selected as testing samples to analyze the relationship between the performance of spectral reconstruction and the different types of training and testing samples. The experimental results showed that the back-propagation (BP) network structure of 3-14-6 and 6 principal components were the best choices. The consistency between training samples and scanned objects was important for the spectral reconstruction of images based on color scanner.