Visual reconstruction with discontinuities using variational methods
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摘要
Visual reconstruction problems tend to be mathematically ill-posed. They can be reformulated as well-posed variational problems using regularization theory. A generalization of the standard regularization method to visual reconstruction with discontinuities leads to variational problems which include the discontinuity contours in their unknowns. The minimization of the corresponding functionals is a difficult problem. This paper suggests the use of the Γ-convergence theory to approximate the functional to be minimized by elliptic functionals, which are more tractable. A Γ-convergence theorem which is of relevance to vision applications is discussed, and the results of computer experiments with both synthetic and real images are shown.
论文关键词:early vision,discontinuity detection,variational convergence
论文评审过程:Received 26 March 1990, Revised 26 February 1991, Available online 14 August 2003.
论文官网地址:https://doi.org/10.1016/0262-8856(92)90081-D