Improved color accuracy of the camera using optimized matching illumination method

To improve the color reproduction and realism of digital cameras and to promote the development of computer vision. Camera colorimetry is conditioned on the spectral sensitivity response of the camera being a linear transformation of the color matching function of the human visual system. Previous methods have proposed placing well-designed filters in front of the camera to produce a sensitivity that well matches the Luther condition. In this paper, we optimize the latest matching illumination method (by using a spectral-tunable illumination system to modulate the spectrum of certain light sources), improve the method of designing filters and add new constraints. Experiments demonstrate that the matching illumination method using new objective functions give a 5% improvement over the original method, and the optimization of the filter using a gradient ascent algorithm and a genetic algorithm gives a 10% improvement in chromaticity over the original method. The method of limiting the average transmittance also has a 10% improvement over the previous one. As a result, these methods can make the imaging of digital cameras more accurate and realistic.