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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 ${\sim}{6.7}\%$ 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 ${{\pm 3}}^\circ$, leading to effectively improved tomographic reconstruction of flame chemiluminescence distribution.
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