期刊
JOURNAL OF MATHEMATICAL IMAGING AND VISION
卷 19, 期 3, 页码 219-235出版社
SPRINGER
DOI: 10.1023/A:1026276804745
关键词
filtering; regularization; bounded variation; segmentation; taut-string algorithm
In this paper tube methods for reconstructing discontinuous data from noisy and blurred observation data are considered. It is shown that discrete bounded variation (BV)-regularization ( commonly used in inverse problems and image processing) and the taut-string algorithm ( commonly used in statistics) select reconstructions in a tube. A version of the taut-string algorithm applicable for higher dimensional data is proposed. This formulation results in a bilateral contact problem which can be solved very efficiently using an active set strategy. As a by-product it is shown that the Lagrange multiplier of the active set strategy is an efficient parameter for edge detection.
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