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Improving results of a simple RGB model for cameras using estimation

The purpose of this paper is to investigate if it is possible to use estimation techniques to reduce the difference between predicted and actual RGB values. Images and spectral reflectances of two classes of objects were used: matte, 2D (Munsell chips and Macbeth chart) and natural, 3D objects (faces). In the prediction phase, a simple RGB model was evaluated which takes into account only the spectral power distributions of the current and calibration illuminants, spectral reflectances of the objects, and the spectral response of the RGB camera in the calculations to avoid the complexity of modeling other possible factors affecting image formation. The results show that an estimation can make the prediction results closer to the actual values.