Affiliation:
1. Beijing Institute of Technology
Abstract
This study reports a new, to the best of our
knowledge, view registration method that can achieve high-quality
tomographic reconstruction in spite of a large view registration (VR)
error. The correlation-based view registration (CBVR) method is a
directional orientation modification method based on the
cross-correlation between measured projections and ray-tracings
generated from the reconstruction, which can reduce the gross VR error
to moderate levels by iterations. In the CBVR method, a traditional
multi-camera VR process is first performed, based on the sensitivity
of the projections to the VR error, and are evaluated and quantified
for all cameras. Afterward, the orientation of each camera is
iteratively updated based on the cross-correlation of the measured
projections and the ray-tracings generated from the reconstruction
calculated through all other cameras. The CBVR is consecutively
validated by numerical and experimental studies. Through a numerical
study on a controlled phantom introduced with 2% Gaussian noise, the
CBVR method is proved to be able to reduce the large VR error (up to
4.8°) to 0.2° as well as to reduce the reconstruction error to
∼
6.7
%
in 12 rounds of iterations, which is
very close to that obtained without any VR error (6% caused by
Gaussian noise only). The CBVR method is then demonstrated and
validated by reconstructing a two-branch laminar flame. By
implementing the method, the initial projection orientations are
optimized from traditional multi-camera VR results within a range of
±
3
∘
, leading to effectively improved
tomographic reconstruction of flame chemiluminescence
distribution.
Funder
National Natural Science Foundation of China
Beijing Municipal Natural Science Foundation
State Key Laboratory of Engines
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
2 articles.
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