title: Robust and accurate transient light transport decomposition via convolutional sparse coding.
abstract: 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.
authors.forename: Xuemei
authors.initials: X
authors.lastname: Hu
authors.forename: Yue
authors.initials: Y
authors.lastname: Deng
authors.forename: Xing
authors.initials: X
authors.lastname: Lin
authors.forename: Jinli
authors.initials: J
authors.lastname: Suo
authors.forename: Qionghai
authors.initials: Q
authors.lastname: Dai
authors.forename: Christopher
authors.initials: C
authors.lastname: Barsi
authors.forename: Ramesh
authors.initials: R
authors.lastname: Raskar