光学仪器, 2018, 40 (6): 75, 网络出版: 2019-01-15
基于核熵成分分析的光谱重建算法研究
Study on spectral reconstruction algorithm based on kernel entropy component analysis
多光谱成像 光谱反射率重建 主成分分析(PCA) 核主成分分析(KPCA) 核熵成分分析(KECA) multi-spectral imaging spectral reflectance reconstruction principal component analysis(PCA) kernel principal component analysis(KPCA) kernel entropy component analysis(KECA)
摘要
对基于核熵成分分析的光谱反射率重建方法进行了研究,分别采用主成分分析方法和核主成分分析方法构建光谱反射率重建算法进行颜色重建研究,并与基于核熵成分分析算法的光谱反射率进行比较。实验结果表明,基于核熵成分分析的光谱重建算法在色度精度和光谱精度上均优于主成分分析和核主成分分析,对物体表面颜色的真实重建具有一定的应用价值。
Abstract
The study worked on the spectral reflectance reconstruction method based on kernel entropy component analysis(KECA).The spectral reflectance reconstruction algorithm was constructed by principal component analysis(PCA) and kernel principal component analysis(KPCA) respectively.Then color reproduction was studied and compared with the spectral reflectance algorithm based on KECA.The results show that the spectral reconstruction algorithm based on KECA is superior to PCA and KPCA in chromaticity accuracy and spectral accuracy.The study shows that KECA is valuable for the real reproduction of the surface color of the object in practice.
杜德伟, 张晓晓, 张洋, 孙山, 韩浩然, 杨卫平. 基于核熵成分分析的光谱重建算法研究[J]. 光学仪器, 2018, 40(6): 75. DU Dewei, ZHANG Xiaoxiao, ZHANG Yang, SUN Shan, HAN Haoran, YANG Weiping. Study on spectral reconstruction algorithm based on kernel entropy component analysis[J]. Optical Instruments, 2018, 40(6): 75.