Imaging in scattering media using correlation image sensors and sparse convolutional coding
Type
ArticleKAUST Department
Computational Imaging GroupComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center (VCC)
Date
2014-10-17Online Publication Date
2014-10-17Print Publication Date
2014-10-20Permanent link to this record
http://hdl.handle.net/10754/556516
Metadata
Show full item recordAbstract
Correlation image sensors have recently become popular low-cost devices for time-of-flight, or range cameras. They usually operate under the assumption of a single light path contributing to each pixel. We show that a more thorough analysis of the sensor data from correlation sensors can be used can be used to analyze the light transport in much more complex environments, including applications for imaging through scattering and turbid media. The key of our method is a new convolutional sparse coding approach for recovering transient (light-in-flight) images from correlation image sensors. This approach is enabled by an analysis of sparsity in complex transient images, and the derivation of a new physically-motivated model for transient images with drastically improved sparsity.Citation
Imaging in scattering media using correlation image sensors and sparse convolutional coding 2014, 22 (21):26338 Optics ExpressPublisher
The Optical SocietyJournal
Optics ExpressAdditional Links
http://www.opticsinfobase.org/abstract.cfm?URI=oe-22-21-26338ae974a485f413a2113503eed53cd6c53
10.1364/OE.22.026338