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Mathematical Morphology and Its Applications to Signal and Image Processing

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Cover of 'Mathematical Morphology and Its Applications to Signal and Image Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Tropical Geometry, Mathematical Morphology and Weighted Lattices
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    Chapter 2 From Structuring Elements to Structuring Neighborhood Systems
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    Chapter 3 Hierarchical Laplacian and Its Spectrum in Ultrametric Image Processing
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    Chapter 4 A Link Between the Multiplicative and Additive Functional Asplund’s Metrics
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    Chapter 5 An Equivalence Relation Between Morphological Dynamics and Persistent Homology in 1D
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    Chapter 6 Dual-Primal Skeleton: A Thinning Scheme for Vertex Sets Lying on a Surface Mesh
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    Chapter 7 Topological Mapper for 3D Volumetric Images
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    Chapter 8 Local Uniqueness Under Two Directions in Discrete Tomography: A Graph-Theoretical Approach
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    Chapter 9 Constructing a Braid of Partitions from Hierarchies of Partitions
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    Chapter 10 Watersheding Hierarchies
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    Chapter 11 On the Probabilities of Hierarchical Watersheds
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    Chapter 12 Incremental Attribute Computation in Component-Hypertrees
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    Chapter 13 Incremental Bit-Quads Count in Tree of Shapes
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    Chapter 14 Matrix Morphology with Extremum Principle
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    Chapter 15 Classification of Hyperspectral Images as Tensors Using Nonnegative CP Decomposition
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    Chapter 16 A Unified Approach to the Processing of Hyperspectral Images
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    Chapter 17 Introducing Multivariate Connected Openings and Closings
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    Chapter 18 Approaches to Multivalued Mathematical Morphology Based on Uncertain Reduced Orderings
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    Chapter 19 Efficient 3D Erosion Dilation Analysis by Sub-Pixel EDT
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    Chapter 20 A Fast, Memory-Efficient Alpha-Tree Algorithm Using Flooding and Tree Size Estimation
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    Chapter 21 Preventing Chaining in Alpha-Trees Using Gabor Filters
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    Chapter 22 A Graph Formalism for Time and Memory Efficient Morphological Attribute-Space Connected Filters
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    Chapter 23 Ultimate Levelings with Strategy for Filtering Undesirable Residues Based on Machine Learning
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    Chapter 24 Max-Plus Operators Applied to Filter Selection and Model Pruning in Neural Networks
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    Chapter 25 Part-Based Approximations for Morphological Operators Using Asymmetric Auto-encoders
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    Chapter 26 Marker Based Segmentation Revisited
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    Chapter 27 Fast Marching Based Superpixels Generation
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    Chapter 28 Characterization and Statistics of Distance-Based Elementary Morphological Operators
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    Chapter 29 Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
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    Chapter 30 Attribute Filtering of Urban Point Clouds Using Max-Tree on Voxel Data
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    Chapter 31 Complementarity-Preserving Fracture Morphology for Archaeological Fragments
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    Chapter 32 Pattern Spectra from Different Component Trees for Estimating Soil Size Distribution
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    Chapter 33 Contact Based Hierarchical Segmentation for Granular Materials
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    Chapter 34 Detecting Branching Nodes of Multiply Connected 3D Structures
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    Chapter 35 Segmenting Junction Regions Without Skeletonization Using Geodesic Operators and the Max-Tree
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    Chapter 36 Multilabel, Multiscale Topological Transformation for Cerebral MRI Segmentation Post-processing
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    Chapter 37 Hierarchical Approach for Neonate Cerebellum Segmentation from MRI: An Experimental Study
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    Chapter 38 Atlas-Based Automated Detection of Swim Bladder in Medaka Embryo
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    Chapter 39 Self-dual Pattern Spectra for Characterising the Dermal-Epidermal Junction in 3D Reflectance Confocal Microscopy Imaging
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    Chapter 40 Spherical Fluorescent Particle Segmentation and Tracking in 3D Confocal Microscopy
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    Chapter 41 Combining Mathematical Morphology and the Hilbert Transform for Fully Automatic Nuclei Detection in Fluorescence Microscopy
Attention for Chapter 41: Combining Mathematical Morphology and the Hilbert Transform for Fully Automatic Nuclei Detection in Fluorescence Microscopy
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Chapter title
Combining Mathematical Morphology and the Hilbert Transform for Fully Automatic Nuclei Detection in Fluorescence Microscopy
Chapter number 41
Book title
Mathematical Morphology and Its Applications to Signal and Image Processing
Published by
Springer, Cham, July 2019
DOI 10.1007/978-3-030-20867-7_41
Book ISBNs
978-3-03-020866-0, 978-3-03-020867-7
Authors

Carl J. Nelson, Philip T. G. Jackson, Boguslaw Obara, Nelson, Carl J., Jackson, Philip T. G., Obara, Boguslaw

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Student > Ph. D. Student 1 20%
Student > Master 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 1 20%
Physics and Astronomy 1 20%
Engineering 1 20%
Unknown 2 40%