Volumetric Data Reduction in a Compressed Sensing Framework
Loading...
Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley and Sons Ltd.
Abstract
In this paper, we investigate compressed sensing principles to devise an in-situ data reduction framework for visualization of volumetric datasets. We exploit the universality of the compressed sensing framework and show that the proposed method offers a refinable data reduction approach for volumetric datasets. The accurate reconstruction is obtained from partial Fourier measurements of the original data that are sensed without any prior knowledge of specific feature domains for the data. Our experiments demonstrate the superiority of surfacelets for efficient representation of volumetric data. Moreover, we establish that the accuracy of reconstruction can further improve once a more effective basis for a sparser representation of the data becomes available.
Description
@article{:10.1111/cgf.12367,
journal = {Computer Graphics Forum},
title = {{Volumetric Data Reduction in a Compressed Sensing Framework}},
author = {Xu, Xie and Sakhaee, Elham and Entezari, Alireza},
year = {2014},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {/10.1111/cgf.12367}
}