Optimization of laser-induced printed colors for industrial applications

Laser-induced printing is an affordable, fast, and non-contact method for creating high-resolution images. Using plasmonic nanocomposite thin films, it enables the printing of color images with visual effects. However, the color gamut of these images is limited compared to inkjet printing. Therefore, it is necessary to optimize this gamut in order to print images that contain the widest range of colors and are closest to the original. There is currently no model to directly infer the color from the laser parameters used. Instead, a lookup table is required to associate these parameters with actual colors. Since colors vary depending on the type of sample used, it is essential to have a reliable method to quickly determine the laser parameters that produce the best colors. Two methods have been implemented to optimize the color gamut: a genetic algorithm approach to find colors that both increase both hue diversity and saturation, and a Bayesian approach to increase the size of the color gamut. Gamut mapping is then used to print the image, and the quality of the final printed image is assessed using metrics obtained from a psychophysical study.