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Imaging the Propagation of Light Through Scenes at Picosecond Resolution

By Andreas Velten, Di Wu, Belen Masia, Adrian Jarabo, Christopher Barsi, Chinmaya Joshi, Everett Lawson, Moungi Bawendi, Diego Gutierrez, Ramesh Raskar

Communications of the ACM, Vol. 59 No. 9, Pages 79-86

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We present a novel imaging technique, which we call femto-photography, to capture and visualize the propagation of light through table-top scenes with an effective exposure time of 1.85 ps per frame. This is equivalent to a resolution of about one half trillion frames per second; between frames, light travels approximately just 0.5 mm. Since cameras with such extreme shutter speed obviously do not exist, we first re-purpose modern imaging hardware to record an ensemble average of repeatable events that are synchronized to a streak sensor, in which the time of arrival of light from the scene is coded in one of the sensor's spatial dimensions. We then introduce reconstruction methods that allow us to visualize the propagation of femtosecond light pulses through the scenes. Given this fast resolution and the finite speed of light, we observe that the camera does not necessarily capture the events in the same order as they occur in reality: we thus introduce the notion of time-unwarping between the camera's and the world's space–time coordinate systems, to take this into account. We apply our femto-photography technique to visualizations of very different scenes, which allow us to observe the rich dynamics of time-resolved light transport effects, including scattering, specular reflections, diffuse interreflections, diffraction, caustics, and subsurface scattering. Our work has potential applications in artistic, educational, and scientific visualizations; industrial imaging to analyze material properties; and medical imaging to reconstruct subsurface elements. In addition, our time-resolved technique has already motivated new forms of computational photography, as well as novel algorithms for the analysis and synthesis of light transport.

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1. Introduction

The way in which light travels through a scene—the paths it follows, how its intensity evolves over time—is an incommensurate source of information on the nature of such scene. From it, we can for instance obtain the geometry of the scene (even of those parts which are not visible to the camera),6, 11, 17 the reflectance of the objects present,12 or even derive other material properties.20 As such, it can play a very important role in a variety of fields, including computer graphics, computer vision, and scientific imaging in general, and have applications in medicine, defense, or industrial processes, to name a few. However, traditionally, light has been assumed to travel instantaneously through a scene (its speed assumed to be infinite), because conventional imaging hardware is very slow compared to the speed of light. Consequently, any information encoded in the time delays of light propagation is lost, and disambiguating light transport becomes an arduous, often impossible, task. In the past years, the joint design of novel optical hardware and smart computation (i.e., computational photography), has expanded the way we capture, analyze, and understand visual information; however, speed-of-light propagation has been largely unexplored at the macroscopic scale, due to the impossibility of capturing such information.


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