Scene illuminant classification: brighter is better

Knowledge of the scene illuminant spectral power distribution is useful for many imaging applications, such as color image reproduction and automatic algorithms for image database applications. In many applications accurate s pectral characterization of the illuminant is impossible because the input device acquires only three spectral samples. In such applications it is sen sible to set a more limited objective of classifying the illuminant as belo nging to one of several likely types. We describe a data set of natural ima ges with measured illuminants for testing illuminant classification algorit hms. One simple type of algorithm is described and evaluated by using the n ew data set. The empirical measurements show that illuminant information is more reliable in bright regions than in dark regions. Theoretical predicti ons of the algorithm's classification performance with respect to scene ill uminant blackbody color temperature are tested and confirmed by using the n atural-image data set. (C) 2001 Optical Society of America.