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Titlebook: Combinatorial Image Analysis; 11th International W Ralf Reulke,Ulrich Eckardt,Konrad Polthier Conference proceedings 2006 Springer-Verlag B

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书目名称Combinatorial Image Analysis
副标题11th International W
编辑Ralf Reulke,Ulrich Eckardt,Konrad Polthier
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Combinatorial Image Analysis; 11th International W Ralf Reulke,Ulrich Eckardt,Konrad Polthier Conference proceedings 2006 Springer-Verlag B
出版日期Conference proceedings 2006
关键词Computer; Fuzzy; algorithms; cognition; combinatorial image analysis; combinatorics; computational geometr
版次1
doihttps://doi.org/10.1007/11774938
isbn_softcover978-3-540-35153-5
isbn_ebook978-3-540-35154-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2006
The information of publication is updating

书目名称Combinatorial Image Analysis影响因子(影响力)




书目名称Combinatorial Image Analysis影响因子(影响力)学科排名




书目名称Combinatorial Image Analysis网络公开度




书目名称Combinatorial Image Analysis网络公开度学科排名




书目名称Combinatorial Image Analysis被引频次




书目名称Combinatorial Image Analysis被引频次学科排名




书目名称Combinatorial Image Analysis年度引用




书目名称Combinatorial Image Analysis年度引用学科排名




书目名称Combinatorial Image Analysis读者反馈




书目名称Combinatorial Image Analysis读者反馈学科排名




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Branch Voxels and Junctions in 3D Skeletonsan space. This paper applies the concept of branch points in the 3D orthogonal grid, motivated by the need to analyze curve-like structures in digital images. These curve-like structures have been derived as 3D skeletons (by means of thinning). This paper discusses approaches of defining branch indi
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Matching of the Multi-channel Images with Improved Nonparametric Transformations and Weighted Binaryits many desirable properties at relatively small computation complexity: It concentrates on capturing mutual relation among pixels in a small neighbourhoods rather than bare intensity values, thus improving matching discrimination. It is also more resistive against noise and uneven lighting conditi
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A New Sub-pixel Map for Image Analysisd to pixel accuracy. This leads to limitations in the representation of complex structures (such as junctions, triangulations, and skeletons) and discards the sub-pixel information available in grayvalue and color images. We extend the planar map formalism to sub-pixel accuracy and introduce various
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Extended Mumford-Shah Regularization in Bayesian Estimation for Blind Image Deconvolution and Segmenoisy images or video sequences. The Mumford-Shah functional is extended to have cost terms for the estimation of blur kernels via a newly introduced prior solution space. This functional is minimized using Γ-convergence approximation in an embedded alternating minimization within Neumann conditions.
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