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Image processing and analysis with g...
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Grady, Leo.
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Image processing and analysis with graphs = theory and practice /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Image processing and analysis with graphs/ edited by Olivier Lzoray, Leo Grady.
其他題名:
theory and practice /
其他作者:
Grady, Leo.
出版者:
Boca Raton, FL :CRC Press, : c2012.,
面頁冊數:
1 online resource (xxiii, 527, [8] p.) :ill. (some col.)
內容註:
1. Graph theory concepts and definitions used in image processing and analysis -- 2. Graph cuts--combinatorial optimization in vision -- 3. Higher-order models in computer vision -- 4. A parametric maximum flow approach for discrete total variation regularization -- 5. Targeted image segmentation using graph methods -- 6. A short tour of mathematical morphology on edge and vertex weighted graphs -- 7. Partial difference equations on graphs for local and nonlocal image processing -- 8. Image denoising with nonlocal spectral graph wavelets -- 9. Image and video matting -- 10. Optimal simultaneous multisurface and multiobject image segmentation -- 11. Hierarchical graph encodings -- 12. Graph-based dimensionality reduction -- 13. Graph edit distance--theory, algorithms, and applications -- 14. The role of graphs in matching shapes and in categorization -- 15. 3D shape registration using spectral graph embedding and probabilistic matching -- 16. Modeling images with undirected graphical models -- 17. Tree-walk kernels for computer vision.
標題:
Computer vision - Mathematics. -
電子資源:
http://www.crcnetbase.com/isbn/9781439855089
ISBN:
9781439855089 (electronic bk.)
Image processing and analysis with graphs = theory and practice /
Image processing and analysis with graphs
theory and practice /[electronic resource] :edited by Olivier Lzoray, Leo Grady. - Boca Raton, FL :CRC Press,c2012. - 1 online resource (xxiii, 527, [8] p.) :ill. (some col.) - Digital imaging and computer vision series. - Digital imaging and computer vision series..
Includes bibliographical references and index.
1. Graph theory concepts and definitions used in image processing and analysis -- 2. Graph cuts--combinatorial optimization in vision -- 3. Higher-order models in computer vision -- 4. A parametric maximum flow approach for discrete total variation regularization -- 5. Targeted image segmentation using graph methods -- 6. A short tour of mathematical morphology on edge and vertex weighted graphs -- 7. Partial difference equations on graphs for local and nonlocal image processing -- 8. Image denoising with nonlocal spectral graph wavelets -- 9. Image and video matting -- 10. Optimal simultaneous multisurface and multiobject image segmentation -- 11. Hierarchical graph encodings -- 12. Graph-based dimensionality reduction -- 13. Graph edit distance--theory, algorithms, and applications -- 14. The role of graphs in matching shapes and in categorization -- 15. 3D shape registration using spectral graph embedding and probabilistic matching -- 16. Modeling images with undirected graphical models -- 17. Tree-walk kernels for computer vision.
"The first book to serve as a comprehensive review of digital imaging and computer vision, this book begins with an introduction chapter to ease readers unfamiliar with concepts into following topics. The book is divided into two parts that focus on the processing of functions on graphs, graph-based image processing, and the representation and analysis of objects on graphs, graph-based image analysis. Each chapter provides a comprehensive review on a specific topic, which ranges from research challenges to industry trends, and provides numerous examples to illustrate how the proposed methods can be used in practice. A companion website is available"--
ISBN: 9781439855089 (electronic bk.)Subjects--Topical Terms:
596840
Computer vision
--Mathematics.
LC Class. No.: TA1634 / .I49 2012eb
Dewey Class. No.: 006.6
Image processing and analysis with graphs = theory and practice /
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1. Graph theory concepts and definitions used in image processing and analysis -- 2. Graph cuts--combinatorial optimization in vision -- 3. Higher-order models in computer vision -- 4. A parametric maximum flow approach for discrete total variation regularization -- 5. Targeted image segmentation using graph methods -- 6. A short tour of mathematical morphology on edge and vertex weighted graphs -- 7. Partial difference equations on graphs for local and nonlocal image processing -- 8. Image denoising with nonlocal spectral graph wavelets -- 9. Image and video matting -- 10. Optimal simultaneous multisurface and multiobject image segmentation -- 11. Hierarchical graph encodings -- 12. Graph-based dimensionality reduction -- 13. Graph edit distance--theory, algorithms, and applications -- 14. The role of graphs in matching shapes and in categorization -- 15. 3D shape registration using spectral graph embedding and probabilistic matching -- 16. Modeling images with undirected graphical models -- 17. Tree-walk kernels for computer vision.
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http://www.crcnetbase.com/isbn/9781439855089
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