title: Computed tomography for high-speed rotation object.
abstract: Computed tomography (CT) for inspecting high-speed rotation objects (HRO) is difficult. Images reconstructed directly by conventional reconstruction algorithms would usually suffer from motion blurring. Currently, studies on this topic are very few. In this paper, we build a mathematical model to describe the scanning data for HRO and establish a principle for choosing the sampling time, which results in a deconvolution model. The idea of split Bregman is utilized to solve the model efficiently. Then, from the deconvoluted data, the image of HRO is reconstructed by conventional reconstruction algorithms. Experiments on simulation data as well as real data are provided to verify the effectiveness of our approach.
authors.forename: Defeng
authors.initials: D
authors.lastname: Chen
authors.forename: Hongwei
authors.initials: H
authors.lastname: Li
authors.forename: Qian
authors.initials: Q
authors.lastname: Wang
authors.forename: Peng
authors.initials: P
authors.lastname: Zhang
authors.forename: Yining
authors.initials: Y
authors.lastname: Zhu