In this paper we propose a new approach for tomographic reconstruction with spatially varying regularization parameter. Our work is based on the SA-TV image restoration model proposed in [3] where an automated parameter selection rule for spatially varying parameter has been proposed. Their parameter selection rule, however, only applies if measured imaging data are defined in image domain, e.g. for image denoising and image deblurring problems. By introducing an auxiliary variable in their model we show here that this idea can indeed by extended to general inverse imaging problems such as tomographic reconstruction where measurements are not in image domain. We demonstrate the validity of the proposed approach and its effectiveness for computed tomography reconstruction, delivering reconstruction results that are significantly improved compared the state-of-the-art.

中文翻译：

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具有空间变化参数选择的断层扫描重建

在本文中，我们提出了一种具有空间变化正则化参数的断层扫描重建新方法。我们的工作基于 [3] 中提出的 SA-TV 图像恢复模型，其中提出了用于空间变化参数的自动参数选择规则。然而，他们的参数选择规则仅适用于在图像域中定义测量成像数据的情况，例如图像去噪和图像去模糊问题。通过在他们的模型中引入一个辅助变量，我们在这里展示了这个想法确实可以扩展到一般的逆成像问题，例如断层扫描重建，其中测量不在图像域中。我们证明了所提出方法的有效性及其对计算机断层扫描重建的有效性，