Optimal illumination spectra for a particular scene

Abstract:Advances in LED and electronic control technologies have enabled the development of multi-channel, color-tunable light sources, offering new possibilities for enhancing the visual attractiveness of objects in applications such as retail and museum lighting. This thesis introduces an object-oriented lighting approach, in which the spectrum of the light source is tailored to the color characteristics of individual objects or a set of objects. At first, a method was proposed to explore the full range of metameric spectra for a particular multi-channel light source and a particular Correlated Color Temperature and illuminance. The impact of each spectrum on the perceived attractiveness was evaluated using a number of psychophysical experiments. It was observed that an "optimum" spectrum, chosen from all the metameric spectra, which renders the object as most attractive can be defined. Further analysis indicates that traditional color rendering metrics such as CIE CRI (Ra) and TM-30 fidelity (Rf) are not strong predictors for selecting this "optimum" spectrum for maximum visual appeal. Instead, hue-specific metrics—particularly local chroma shift —correlate more strongly with attractiveness. A prototype lighting system was developed, featuring a six-channel LED luminaire, custom driver, wireless control, and a neural network-based mobile app for hue bin classification of the illuminated object. Finally, an exploitation plan has been developed. Initial user feedback suggests strong potential for real-world implementation and commercialization.

Publication year:2025

Accessibility:Embargoed