Abstract

We have determined the reflectance spectra of colored metallic coatings with high spatial resolution by using a hyperspectral imaging system. Reflectance spectra were converted to color coordinates revealing characteristic color maps in the color space. Principal-component analysis was applied to decorrelate the spatial variability of the reflectance spectra. We found that the eigenvalue spectra follow different power laws. The scaling exponent was analyzed by considering random-walk-type processes. An estimation of the Hurst exponent was done, suggesting anomalous diffusion from multiple light scattering. The results show that hyperspectral imaging combined with principal-component analysis provides a valuable method for nondestructive testing of complex turbid media.

© 2011 Optical Society of America

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