Recovery of camera spectral sensitivity based on multi-objective optimization method

The accurate prediction of spectral sensitivity of digital camera is essential for various aspects in color science, such as color correction, color rendering and color constancy. In this paper, a multi-objective optimization algorithm was proposed to estimate the spectral sensitivity of cameras. Multiple objective functions and Sine subspace based spectral sensitivity were employed in the proposed algorithm, in which excellent robustness and high smoothness were achieved. The performance of this algorithm was theoretically evaluated by multiple numerical simulation experiments, and was further compared with other algorithms in previous literatures based on the criteria of color aberration (δE), spectral recovery error (SE) and similarity between the estimated sensors and the measured ground truth (Vora). According to the numerical simulation results, the multi-objective algorithm can significantly improve the performance of the spectral sensitivity estimation, which may promote its various applications in the fields of color correction and illumination modeling between cameras.