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 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 . The discrete-time samples are processed to obtain -regularized estimates of . Improving on previous work, using nonimpulsive, bandlimited light sources instead of impulsive illumination significantly improves signal-to-noise ratio (SNR) and reconstruction quality. Our simulations suggest that practical diffuse imaging applications may be realized with commercially-available temporal light intensity modulators and sensors used in standard optical communication systems.
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