Abstract
We describe a computational imaging system for x-ray tomography, where image capture and post-processing are co-designed to improve final image quality when relative motion of an experiment’s components during a single exposure causes motion blur. The idea is based on temporally encoding the motion during each exposure by fluttering the detector shutter open and closed with a known sequence for guaranteeing an invertible motion blur kernel. While generally applicable, we demonstrate our approach by simulating blurry data acquisition for transmission x-ray tomography and deblurring the reconstructed images. The results suggest that optimized pseudo-random binary time-coded apertures can yield successful reconstructions independent of the size of the blur kernel. This Letter is especially relevant to high-speed x-ray tomography applications where time-resolution is limited by the detector or available photon flux.
© 2019 Optical Society of America
Full Article | PDF ArticleMore Like This
David J. Brady, Daniel L. Marks, Kenneth P. MacCabe, and Joseph A. O’Sullivan
Appl. Opt. 52(32) 7745-7754 (2013)
Zhihong Zhang, Kaiming Dong, Jinli Suo, and Qionghai Dai
Photon. Res. 11(10) 1678-1686 (2023)
Kenneth MacCabe, Kalyani Krishnamurthy, Amarpreet Chawla, Daniel Marks, Ehsan Samei, and David Brady
Opt. Express 20(15) 16310-16320 (2012)