A New Spectral Clustering Analysis Method Based on First Derivative
By extending the number of signal channels to high dimensions, the multispectral imaging technology fulfils the spectral color reproduction. However, it also brings out calculating and storing problem because of the large spectral database. The solution for this matter is to divide the database into several subgroups and find their basic components for each individual subgroup for linear representation 1. A new approach was proposed for grouping similar spectrum from spectral database. Based on the first derivative of each spectral curve, we used agglomerative hierarchical cluster analysis to divide the database into ten groups and found their basic components by principal component analysis. The pseudo inverse method was employed to reconstruct the spectral reflectance and the results are compared to three related methods. In the experiment, we grouped the 1250 matt Munsell color chips and the 1600 glossy Munsell color chips to compare the performance of different methods. The results proved that the proposed method outperformed others and showed excellent spectral and colorimetric accuracy.
XiaoXia Wan Qiang Liu
Department of Printing and Packaging, Wuhan University Wuhan, Hubei Province, P.R.China Department of Printing and Packaging, Wuhan University Wuhan, Hubei Province, P.R.China
国际会议
The 31st International Congress on Imaging Science(第31届国际影像科学大会 ICIS2010)
北京
英文
447-450
2010-05-12（万方平台首次上网日期，不代表论文的发表时间）