Development and validation of a reconstruction algorithm for three-dimensional nonlinear tomography problems

Abstract

This work reports the development and experimental validation of a reconstruction algorithm for three-dimensional (3D) nonlinear tomography problems. Many optical tomography problems encountered in practice are nonlinear, for example, due to significant absorption, multiple-scattering, or radiation trapping. Past research efforts have predominately focused on reconstruction algorithms for linear problems, and these algorithms are not readily extendable to nonlinear problems due to several challenges. These challenges include the computational cost caused by the nonlinearity (which was compounded by the large scale of the problems when they are 3D), the limited view angles available in many practical applications, and the measurement uncertainty. A new algorithm was therefore developed to overcome these challenges. The algorithm was validated both numerically and experimentally, and was demonstrated to be able to solve a range of nonlinear tomography problems with significantly enhanced efficiency and accuracy compared to existing algorithms.

Investigation of flame radiation sampling and temperature measurement through light field camera

“…However, it is significantly important to investigate which light field camera can provide better reconstruction accuracy and reliability for the flame temperature measurement. Because the accurate and reliable 3-D measurements of the flame temperature are crucial for improving the combustion efficiency and controlling the combustion products such as NOx and particulate matter [10,11].…”

Development of an absorption-corrected method for 3D computed tomography of chemiluminescence

“…Therefore, each iteration in the tomographic algorithm needs four steps: the first is to update the attenuation coefficients, which are proportional to the distributions of chemiluminescence; the second is to calculate the re-projection based on the chemiluminescent distribution in the previous step; the third is to calculate the correction term; and the fourth is to update the current chemiluminescent distribution. In contrast to the work by Lei et al [20], the weight coefficients remain the same throughout the whole iterative process.…”

“…Prior to our work, Lei et al developed and validated a reconstruction algorithm for nonlinear tomography problems involving significant absorption, multiple-scattering, or radiation trapping [20]. However, this work is mostly performed under the context of volumetric laser-induced fluorescence (LIF) measurements, and the incident laser intensity was also included in the imaging model.…”

Spatiotemporal flame mapping in a large-bore marine diesel engine using multiple high-speed cameras

“…Many alternative solutions exist in the algebraic formulation and multiple algorithms have been developed and evaluated throughout the years. 34–39 The one most commonly used is the algebraic reconstruction technique (ART) that provides consistent results at a relatively low computational cost.…”