By Olivier Lezoray, Leo Grady
ISBN-10: 1439855080
ISBN-13: 9781439855089
Covering the theoretical elements of picture processing and research by utilizing graphs within the illustration and research of items, Image Processing and research with Graphs: thought and Practice additionally demonstrates how those thoughts are indispensible for the layout of state of the art recommendations for real-world applications.
Explores new purposes in computational images, photo and video processing, special effects, reputation, scientific and biomedical imaging
With the explosive development in photograph creation, in every thing from electronic pictures to scientific scans, there was a drastic elevate within the variety of purposes in line with electronic photos. This publication explores how graphs―which are compatible to symbolize any discrete information via modeling local relationships―have emerged because the excellent unified software to symbolize, technique, and learn photographs. It additionally explains why graphs are perfect for defining graph-theoretical algorithms that permit the processing of capabilities, making it attainable to attract at the wealthy literature of combinatorial optimization to supply hugely effective solutions.
Some key matters coated within the ebook include:
- Definition of graph-theoretical algorithms that permit denoising and snapshot enhancement
- Energy minimization and modeling of pixel-labeling issues of graph cuts and Markov Random Fields
- Image processing with graphs: detailed segmentation, partial differential equations, mathematical morphology, and wavelets
- Analysis of the similarity among items with graph matching
- Adaptation and use of graph-theoretical algorithms for particular imaging purposes in computational images, computing device imaginative and prescient, and scientific and biomedical imaging
Use of graphs has turn into very influential in laptop technological know-how and has ended in many functions in denoising, enhancement, recovery, and item extraction. Accounting for the big variety of difficulties being solved with graphs in photo processing and desktop imaginative and prescient, this e-book is a contributed quantity of chapters written by way of popular specialists who handle particular thoughts or functions. This state of the art evaluation offers software examples that illustrate sensible program of theoretical algorithms. priceless as a aid for graduate classes in snapshot processing and laptop imaginative and prescient, it's also excellent as a reference for working towards engineers engaged on improvement and implementation of photo processing and research algorithms.
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Additional info for Image processing and analysis with graphs : theory and practice
Sample text
1 Globally Minimizable Case: Energies with Convex Prior . . . . . . 2 Move-Making Algorithms . . . . . . . . . . . . . . . . . . . . . 1 α-β Swap and α-Expansion . . . . . . . . . . . . . . . . 2 Fusion Moves . . . . . . . . . . . . . . . . . . . . . . . 3 α-β Range Moves . . . . . . . . . . . . . . . . . . . . . 4 Higher-Order Graph Cuts . . . . . . . . . . . . . . . . . 5 Examples .
Each connected component is a connected graph. The connected components of a graph G are the set of largest subgraphs of G that are each connected. Two nodes are strongly connected if ∃π(vi , vj ) and ∃π(vj , vi ). If two nodes are 9 Graph theory concepts and definitions used in image processing and analysis connected but not strongly connected, then the nodes are called weakly connected. Note that, in an undirected graph, all connected nodes are strongly connected. The graph is strongly connected iff ∀vi , vj ∈ V, ∃π(vi , vj ), and ∃π(vj , vi ).
15 Some proximity graph examples on real-world data. -L. Barabasi, Linked: How Everything Is Connected to Everything Else and What It Means. Plume, New-York, 2003. [3] D. J. Watts, Six Degrees: The Science of a Connected Age. W. W. Norton, 2004. [4] N. A. Christakis and J. H. Fowler, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. Little, Brown and Company, 2009. [5] F. Harary, Graph Theory. Addison-Wesley, 1994. [6] A. Gibbons, Algorithmic Graph Theory. Cambridge University Press, 1989.