Multiplexing for optimal lighting.

Imaging of objects under variable lighting directions is an important and frequent practice in computer vision, machine vision, and image-based rendering. Methods for such imaging have traditionally used only a single light source per acquired image. They may result in images that are too dark and noisy, e.g., due to the need to avoid saturation of highlights. We introduce an approach that can significantly improve the quality of such images, in which multiple light sources illuminate the object simultaneously from different directions. These illumination-multiplexed frames are then computationally demultiplexed. The approach is useful for imaging dim objects, as well as objects having a specular reflection component. We give the optimal scheme by which lighting should be multiplexed to obtain the highest quality output, for signal-independent noise. The scheme is based on Hadamard codes. The consequences of imperfections such as stray light, saturation, and noisy illumination sources are then studied. In addition, the paper analyzes the implications of shot noise, which is signal-dependent, to Hadamard multiplexing. The approach facilitates practical lighting setups having high directional resolution. This is shown by a setup we devise, which is flexible, scalable, and programmable. We used it to demonstrate the benefit of multiplexing in experiments.