Abstract
Projection data obtained through optical techniques for tomographic measurements, such as interferometry for refractive-index-based measurements, are often incomplete. This is due to limitations in the optical system, data storage, and alignment and vignette issues. Algebraic iterative reconstruction techniques are usually favored for such incomplete projections. A number of iterative algorithms, based on additive and multiplicative corrections, are used with a known simulated phantom and noise source to assess the reconstruction performance of incomplete data sets. In addition, we present reconstructions using experimental data obtained from a coherent gradient sensing interferometer for a steady temperature field in a fluid medium. We tested the algorithms using the simulated data set for incompleteness conditions similar to those found in the experimental data, and the best-performing algorithm is identified.
© 2004 Optical Society of America
Full Article | PDF ArticleMore Like This
Dean Verhoeven
Appl. Opt. 32(20) 3736-3754 (1993)
Yao Hongbing, Zhang Yongkang, Ye Xia, and He Anzhi
Appl. Opt. 47(13) 2371-2375 (2008)
Yang Song, Bin Zhang, and Anzhi He
Appl. Opt. 45(31) 8092-8101 (2006)