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E-raamat: Geometric Description of Images as Topographic Maps

  • Formaat: PDF+DRM
  • Sari: Lecture Notes in Mathematics 1984
  • Ilmumisaeg: 24-Dec-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642046117
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  • Formaat: PDF+DRM
  • Sari: Lecture Notes in Mathematics 1984
  • Ilmumisaeg: 24-Dec-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642046117

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This book discusses the basic geometric contents of an image and presents a treedatastructuretohandleite ciently.Itanalyzesalsosomemorphological operators that simplify this geometric contents and their implementation in termsofthe datastructuresintroduced.It nallyreviewsseveralapplications to image comparison and registration, to edge and corner computation, and the selection of features associated to a given scale in images. Let us ?rst say that, to avoid a long list, we shall not give references in this summary; they are obviously contained in this monograph. A gray level image is usually modeled as a function de ned in a bounded N domain D? R (typically N = 2 for usual snapshots, N=3formedical images or movies) with values in R. The sensors of a camera or a CCD array transform the continuum of light energies to a ?nite interval of values by means of a nonlinear function g. The contrast change g depends on the pr- ertiesofthesensors,butalsoontheilluminationconditionsandthere ection propertiesofthe objects,andthoseconditionsaregenerallyunknown.Images are thus observed modulo an arbitrary and unknown contrast change.
Introduction
1(8)
Morse Theory and Topography
1(2)
Mathematical Morphology
3(1)
Inclusion Tree of Level Sets
4(1)
Topological Description and Computation of Topographic Maps
5(1)
Organization of These Notes
6(3)
The Tree of Shapes of an Image
9(26)
Introduction and Motivation
9(2)
Some Topological Preliminaries
11(7)
The Tree of Shapes
18(6)
Tree Structure of the Set of Shapes
19(1)
Branches, Monotone Sections and Leaves
20(4)
Reconstruction of the Image From Its Tree
24(4)
Direct Reconstruction
25(2)
Indirect Reconstruction
27(1)
Finiteness of the Tree for Images with Grains of Minimal Positive Size
28(2)
Applications
30(3)
A Simple Application: Adaptive Quantization
30(1)
Other Applications
31(2)
Comparison with Component Tree
33(2)
Grain Filters
35(40)
Introduction
35(1)
General Results From Mathematical Morphology
36(2)
Level Sets and Contrast Invariance
37(1)
Link Between Set Operator and Contrast Invariant Operators on Images
38(1)
Extrema Filters
38(14)
Definition
39(1)
Preliminary Results
40(3)
Properties
43(3)
Interpretation
46(1)
Composition
46(2)
The Effect of Extrema Filters on the Tree of Shapes
48(4)
Grain Filter
52(13)
Introduction and Definitions
52(2)
Preliminary Results
54(4)
Properties
58(6)
The Effect of Grain Filter on the Tree of Shapes
64(1)
Relations with Other Operators of Mathematical Morphology
65(5)
Relations with Grain Operators
65(1)
Relations with Connected Operators
66(4)
Interpretation
70(1)
Experiments
70(5)
Algorithm
70(1)
Experimental Results
70(3)
Complexity
73(2)
A Topological Description of the Topographic Map
75(28)
Monotone Sections and Singular Values
75(6)
Weakly Oscillating Functions, Their Intervals and the Structure of Their Topographic Map
81(10)
Signature and Critical Values
91(4)
Critical Versus Singular Values
95(2)
Singular Values of the Tree Versus Singular Values
97(3)
Review on the Topographic Description of Images
100(3)
Merging the Component Trees
103(12)
The Structure of the Trees of Connected Components of Upper and Lower Level Sets
103(3)
Construction of the Tree of Shapes by Fusion of Upper and Lower Trees
106(6)
Fusion Algorithm in the Discrete Digital Case
112(3)
Computation of the Tree of Shapes of a Digital Image
115(26)
Continuous Interpretation of a Digital Image
115(3)
From Digital to Continuous Image
115(1)
Digital Shapes
116(2)
Fast Level Set Transform
118(16)
Input and Output
118(1)
Description of the Algorithm
119(9)
Justification of the Algorithm
128(3)
Complexity
131(3)
Comparison to Component Tree Extraction
134(1)
Taking Advantage of the Tree Structure
134(3)
Storage of Pixels of the Digital Shapes
135(1)
Computation of Additive Shape Characteristics
135(2)
Alternative Algorithms
137(4)
Changing Connectivity
137(2)
Level Lines Extraction
139(1)
Higher Dimension
140(1)
Computation of the Tree of Bilinear Level Lines
141(14)
Level Lines and Bilinear Interpolation
141(4)
Tree of Bilinear Level Lines
145(2)
Algorithms for the Extraction of the Tree of Bilinear Level Lines (TBLL)
147(8)
Direct Algorithm
148(2)
Morse Algorithm
150(5)
Applications
155(18)
Image Filters
155(1)
Image Registration
156(8)
Shapes as Features and Their Descriptors
157(1)
Meaningful Matches
158(1)
Grouping Matches
159(1)
Eliminating Outliners by Vote
160(1)
Examples
161(3)
Other Applications
164(3)
Image Intersection
164(1)
Meaningful Edges
164(1)
Corner Detection
165(2)
Scale Adaptive Neighborhoods
167(1)
Maximally Stable Extremal Regions
167(6)
Conclusion
173(4)
Summary
173(1)
Extensions
173(4)
Self-Dual Filters
174(1)
Fast Level Set Transform in Dimension 3
174(1)
Color Images
175(2)
Glossary 177(2)
References 179(6)
Index 185