DocumentCode :
248155
Title :
Real-time compressed imaging of scattering volumes
Author :
Menashe, Ohad ; Bronstein, Alexander
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
1322
Lastpage :
1326
Abstract :
We propose a method and a prototype imaging system for real-time reconstruction of volumetric piecewise-smooth scattering media. The volume is illuminated by a sequence of structured binary patterns emitted from a fan beam projector, and the scattered light is collected by a two-dimensional sensor, thus creating an under-complete set of compressed measurements. We show a fixed-complexity and latency reconstruction algorithm capable of estimating the scattering coefficients in real-time. We also show a simple greedy algorithm for learning the optimal illumination patterns. Our results demonstrate faithful reconstruction from highly compressed measurements. Furthermore, a method for compressed registration of the measured volume to a known template is presented, showing excellent alignment with just a single projection. Though our prototype system operates in visible light, the presented methodology is suitable for fast x-ray scattering imaging, in particular in real-time vascular medical imaging.
Keywords :
data compression; greedy algorithms; image coding; image reconstruction; image sensors; image sequences; light scattering; optical projectors; fan beam projector; fast X-ray scattering imaging; fixed-complexity algorithm; greedy algorithm; image registration; latency image reconstruction algorithm; light scattering; optimal illumination pattern; real-time image compression; real-time vascular medical imaging; scattering volume; structured binary pattern sequence; two-dimensional sensor; volumetric piecewise-smooth scattering media reconstruction; Approximation algorithms; Approximation methods; Image reconstruction; Scattering; Sensors; Tomography; compressive sensing; scattering tomography; sparse coding; structured light; volumetric reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025264
Filename :
7025264
Link To Document :
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