Cycle time reduction in process integrated computed tomography using compressed sensing
In this contribution we investigate whether reconstruction algorithms for X-ray computed tomography (CT) based on the compressed sensing approach are applicable to reduce the cycle time for process integrated CT inspection. In particular we study how the image quality degrades when obtained from fewer projections and a low-complexity reconstruction algorithm (i.e., using only a few iterations). For this purpose, we analyze the convergence behavior using different parameter choices for the reconstruction algorithm and demonstrate the benefits of applying prior knowledge of the specimen. The performance of the studied approaches is evaluated on real measurement data obtained from a large number of combustion motor pistons.