Computational color constancy or white balancing methods for digital cameras emulate the ability of the human visual system to adapt to different lighting situations and to maintain color constancy. Global white balancing algorithms have been shown to give remarkable results for scenes illuminated by one light source, but proven less adequate for multi-illumination scenes where multiple light sources are present. Using information from an additional near-infrared channel can be used to estimate the white point at every pixel in the image by comparing the pixels' NRGB values to a multi-dimensional lookup table with precomputed NRGB values. This estimated white point can then be used for white balancing via linearized Bradford transform. The lookup table requires measurement of multiple reflectance and illumination spectra that are representative for an office environment. The method performs better than conventional global white balancing methods.