【摘 要】
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I will start with a brief review of existing models(both classical and recent)for solving ill-posed linear inverse problems,that include wavelet frame based
【出 处】
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Computational Biomedical Imaging Workshop(2015计算生物医学成像研讨会)
论文部分内容阅读
I will start with a brief review of existing models(both classical and recent)for solving ill-posed linear inverse problems,that include wavelet frame based approach,variational and nonlinear PDE based models.Connections among all these methods will be discussed.In particular,connections of wavelet frame based approach to the total variation model(ROF),Mumford-Shah model,and anisotropic diffusions are established.We will see that wavelet frame transforms are discretization of differential operators in both variational and PDE frameworks,and such discretization is superior to some of the traditional finite difference schemes for some linear inverse problems.Such connections not only lead to new understandings of these popular methods,but also give birth to new models and algorithms for linear inverse problems.If time allows,I will present one specific application at the end of my talk: CT image reconstruction with Radon domain inpainting.
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