Abstract
X-ray Computed Tomography (xCT) is a very effective way of detecting and characterizing the internal information of objects. However, blur is frequent in high-energy industrial xCT (ixCT), degrading image quality and spatial resolution. Therefore, this paper explores the application of L0 regularization to image deblurring in ixCT. With sparsity information of both intensity image and gradient image, the blur is alleviated and both image quality and porosity identification are improved. The method is validated through real ixCT experiments of an additively manufactured component.
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