Titlebook: Geometry-Driven Diffusion in Computer Vision; Bart M. Haar Romeny Book 1994 Springer Science+Business Media Dordrecht 1994 Diffusion.Optim

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Countermand

会议

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绝缘

Stricture

发芽

Macroeconomic and Policy Models,han the inner scale (corresponding to the pixel size,) of the image, these operators always incorporate some averaging or similar mechanism for suppressing fine scale variations. As a consequence the detected edges get blurred and may be displaced. These problems can be circumvented by applying some

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Trade and Competition in the Nordic Contextenotes Lebesgue measure, . is the observed grey level image, i.e., a real valued function, . approximates ., . denotes the set of edges (a closed set), | . | is the total length. of ., and . and . are real positive scalars. This approach is a modification of one due to Geman and Geman [132] that use

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https://doi.org/10.1007/978-1-4419-5612-5ving smoothing. The basic idea is that several maps describing the image, undergo coupled development towards an equilibrium state, repre- senting the enhanced image. These maps could e.g. contain intensity, local edge strength, range, or another quantity. All these maps, including the edge map, con

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