Perception-based lighting design approaches model image quality using a cognitively grounded objective function which is in turn optimized through manipulation of the lighting parameters of a scene. We present, and demonstrate, a detailed implementation of perception-based lighting design, including the application and evaluation of stochastic optimization using genetic algorithms.

Lighting, and its emergence as a digital and networked medium, represents an ideal platform for conducting research on both sensor and human-derived methods of control. Notably, solid-state lighting makes possible the control of the intensity, spatial, and color attributes of lighting in real-time. This technology provides an excellent opportunity to conduct new experiments designed to study ho...