Using alternating least square and regression techniques for the characterization of digital cameras in non-uniform illumination conditions

In the characterization of a digital camera, which is used for the capturing image of natural scenes, removing the illumination non-uniformity is usually done by acquiring the RGB values of the image of a grey card. As this method of characterization is difficult to be performed accurately, in this research an alternating least squares, ALS, technique followed by a polynomial regression technique, called combined method, was used for the characterization of a Nikon D200 digital camera. Also, each of the techniques, ALS and polynomial regression, were done separately for the characterization of the digital camera. The results showed that the performance of the combined method is acceptable and the combined method outperforms the two other methods.