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.
In this paper, the current technologies in full colour 3D printing technology were introduced. A framework of colour image reproduction process for 3D colour printing is proposed. A special focus was put on colour management for 3D printed objects. Two approaches, colorimetric colour reproduction and spectral based colour reproduction are proposed in order to faithfully reproduce colours in 3D objects. Two key studies, colour reproduction for soft tissue prostheses and colour uniformity correction across different orientations are described subsequently. Results are clear shown that applying proposed colour image reproduction framework, performance of colour reproduction can be significantly enhanced. With post colour corrections, a further improvement in colour process are achieved for 3D printed objects.