Optical Splitting Trees for High-Precision Monocular Imaging
This paper introduces a framework to design optical splitting tree to perform computational photography tasks that require many sensors with a common optical axis. As the number of sensors increases, designing a good optical system is often difficult because the components have non-ideal characteristics. We describe an optimization tool takes this into account and finds ``good'' designs as specified by several weighted coefficients. Assisted by this optimizer, we demonstrate high-dynamic range, focusing, matting, high-speed, and hybrid imaging implemented on a single, reconfigurable camera containing eight sensors.