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Optics Letters

Optics Letters


  • Editor: Xi-Cheng Zhang
  • Vol. 39, Iss. 11 — Jun. 1, 2014
  • pp: 3177–3180

Robust and accurate transient light transport decomposition via convolutional sparse coding

Xuemei Hu, Yue Deng, Xing Lin, Jinli Suo, Qionghai Dai, Christopher Barsi, and Ramesh Raskar  »View Author Affiliations

Optics Letters, Vol. 39, Issue 11, pp. 3177-3180 (2014)

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Ultrafast sources and detectors have been used to record the time-resolved scattering of light propagating through macroscopic scenes. In the context of computational imaging, decomposition of this transient light transport (TLT) is useful for applications, such as characterizing materials, imaging through diffuser layers, and relighting scenes dynamically. Here, we demonstrate a method of convolutional sparse coding to decompose TLT into direct reflections, inter-reflections, and subsurface scattering. The method relies on the sparsity composition of the time-resolved kernel. We show that it is robust and accurate to noise during the acquisition process.

© 2014 Optical Society of America

OCIS Codes
(100.3190) Image processing : Inverse problems
(150.1135) Machine vision : Algorithms
(070.2025) Fourier optics and signal processing : Discrete optical signal processing

ToC Category:
Fourier Optics and Signal Processing

Original Manuscript: January 16, 2014
Revised Manuscript: April 14, 2014
Manuscript Accepted: April 16, 2014
Published: May 23, 2014

Xuemei Hu, Yue Deng, Xing Lin, Jinli Suo, Qionghai Dai, Christopher Barsi, and Ramesh Raskar, "Robust and accurate transient light transport decomposition via convolutional sparse coding," Opt. Lett. 39, 3177-3180 (2014)

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