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Making saturated facial images useful again

Saturation here refers to electronic saturation of the camera sensors which produces clipped colors, and not the purity of color as in the hue-saturation and value scale. Saturated images are routinely discarded in image analysis yet there are situations when they cannot be avoided. This paper proposes two strategies to recover color information in facial images taken under non-ideal conditions to make them useful for further processing. The first assumes that the skin is matte and that there are parts of the image which are not clipped. Ratios between R, G and B values of unclipped pixels belonging to the same parts of the image may then be used to compute for lost channel values. The second approach uses color eigenfaces computed from our physics-based face database obtained under different illuminants and camera calibration conditions. Skin color is recovered by transforming the first few eigenface coefficients towards ideal condition values. Excellent color recovery for clipped images is achieved when these two techniques are combined and used on face images captured under daylight illuminant with a camera white balanced for incandescent light.