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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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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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發(fā)表于 2025-3-26 09:31:29 | 只看該作者
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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發(fā)表于 2025-3-26 15:17:32 | 只看該作者
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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