Diffuse imaging: Replacing lenses and mirrors with omnitemporal cameras

Abstract

Conventional imaging uses steady-state illumination and light sensing with focusing optics; variations of the light field with time are not exploited. We develop a signal processing framework for estimating the reflectance f of a Lambertian planar surface in a known position using omnidirectional, time-varying illumination and unfocused, time-resolved sensing in place of traditional optical elements such as lenses and mirrors. Our model associates time sampling of the intensity of light incident at each sensor with a linear functional of f. The discrete-time samples are processed to obtain ℓ2-regularized estimates of f. Using non-impulsive, bandlimited light sources instead of impulsive illumination significantly improves signal-to-noise ratio (SNR) and reconstruction quality.