A step by step recovery of spectral data from colorimetric information

摘要

In this paper, a technique named step by step progressive method is devised for recovery of spectral data from the corresponding colorimetric information. The method consists of several stages and employs different techniques, each of which is used to enhance the performance of the recovery as much as possible. The method firstly tests a series of 6 to 3 dimensional linear interpolation techniques, successively; however, there are some samples lying outside the interpolation color gamut, which is the weakest point of the interpolation method, limiting the performance of the first solution. To overcome this problem, a modified version of weighted principal component analysis (wPCA) is employed for the spectral recovery of the samples that have been failed with linear interpolation approach. The employed weighting function takes the spectral distances of the target data and the learning set into accounts. The efficiency of the method is then evaluated by the spectral and colorimetric deviations between the actual and recovered reflectance spectra and is compared with those obtained by classical 3D linear interpolation and PCA methods. As results show that the proposed progressive approach achieves significant improvement in terms of both spectral and colorimetric errors in comparison to the classical methods.