Camera spectral sensitivity (CSS) establishes the connection between scene radiance and device-captured RGB tristimulus values. Since the spectral sensitivity of most color imaging devices typically deviates from that of human vision or a standard color space and also noise is often introduced during the process of photoelectric signal conversion and transmission, the design of an efficient CSS with noise robustness and high color fidelity is of paramount importance. In this paper, we propose a CSS optimization method with noise consideration that designs theoretically an optimal CSS for each noise level. Additionally, taking practical considerations into account, we further extend the proposed method for a universally optimal CSS adaptable to diverse noise levels. Experimental results show that our optimized CSS is more robust to noise and has better imaging performance than existing optimization methods based on a fixed CSS. The source code is available at https://github.com/xyu12/Joint-Design-of-CSS-and-CCM-with-Noise-Consideration-EI2024.
Advancing in inkjet fused deposition modeling (FDM) color 3D printing enables to create dedicated aesthetical appeal. However, the complete fabrication of a target color remains limited due to the unusual mismatch in 3D color management systems. In particular, the 3D aspect that makes the 3D color systems different from standard 2D printing, such as ink and substrate characteristics, viewing conditions, and base materials. Therefore, to the best of our knowledge, there is no suitable established method that supports color reproduction for inkjet FDM color 3D printing. In this paper, we analyze the color profile of an inkjet FDM color 3D printer to obtain a color model that could bridge the gap between a digital design (as an input) and the actual 3D printed results (as an output). We then created the color model by reproducing each color mapped to every possible color pair to determine the closest color between the target and printing colors on the basis of the color difference value, which can be rendered in lieu of the original printing colors. We verify our proposed color model by printing the mapped color and conduct a color measurement to compare it with the target colors. From the experimental results, we showed that our mapped colors can represent those desired by the user with an 80% success rate, which can be matched through controlled conditions.