Compression of Spectral Data Using Box-Cox Transformation

The principal component analysis technique is used for the compression of different spectral databases including the reflectance spectra of nonfluorescent surfaces as well as the spiky spectra of the total radiance factors of fluorescent samples. Before extraction of principal directions, the Box-Cox transformation technique is used in its original as well as modified version to improve the efficiency of employed compression technique by increasing the degree of normality in the datasets. The employed techniques are evaluated in terms of spectral dissimilarity between the reconstructed and the actual spectra and colorimetric differences by the value of CIELAB color differences of them under D65 and A illuminants and 1964 standard observer. The datasets departures from normal distribution are also investigated. The results confirm the effectiveness of the Box-Cox modification technique for the reducing of spectral dimensions of samples. (c) 2012 Wiley Periodicals, Inc.