Principles of Digital Image Processing: Advanced Methods
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Medienkombination Buch |
| Sprache: | English |
| Veröffentlicht: |
London
Springer
2013
|
| Ausgabe: | 1. Aufl. |
| Schriftenreihe: | Undergraduate Topics in Computer Science
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XIII, 369 S. Ill., graph. Darst. 235 mm x 178 mm |
| ISBN: | 9781848829183 9781848829190 |
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MARC
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| 245 | 1 | 0 | |a Principles of Digital Image Processing |b Advanced Methods |c Wilhelm Burger ; Mark J. Burge |
| 250 | |a 1. Aufl. | ||
| 264 | 1 | |a London |b Springer |c 2013 | |
| 300 | |a XIII, 369 S. |b Ill., graph. Darst. |c 235 mm x 178 mm | ||
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Datensatz im Suchindex
| _version_ | 1804152043391156224 |
|---|---|
| adam_text | Contents
Preface
.........................................................
v
1.
Introduction
................................................ 1
2.
Automatic
Thresholding
.................................... 5
2.1
Global
histogram-based thresholding
........................ 6
2.1.1
Statistical information from the histogram
............. 8
2.1.2
Simple threshold selection
........................... 10
2.1.3
Iterative threshold selection
(ISODATA
algorithm)
..... 11
2.1.4
Otsu s method
..................................... 14
2.1.5
Maximum entropy thresholding
...................... 18
2.1.6
Minimum error thresholding
......................... 22
2.2
Local adaptive thresholding
................................ 30
2.2.1
Bernsen s method
.................................. 30
2.2.2
Niblack s method
................................... 34
2.3
Java implementation
...................................... 46
2.4
Summary and further reading
.............................. 49
2.5
Exercises
................................................ 49
3.
Filters for Color Images
.................................... 51
3.1
Linear filters
............................................. 51
3.1.1
Using monochromatic linear filters on color images
..... 52
3.1.2
Color space considerations
........................... 55
3.2
Non-linear color filters
.................................... 66
3.2.1
Scalar median filter
................................. 66
3.2.2
Vector median filter
................................ 67
3.2.3
Sharpening vector median filter
...................... 69
3.3
Java implementation
...................................... 76
3.4
Further reading
.......................................... 80
3.5
Exercises
................................................ 80
4.
Edge Detection in Color Images
............................ 83
4.1
Monochromatic techniques
................................. 84
4.2
Edges in vector-valued images
.............................. 88
4.2.1
Multi-dimensional gradients
......................... 88
4.2.2
The Jacobian matrix
................................ 93
4.2.3
Squared local contrast
.............................. 94
4.2.4
Color edge magnitude
............................... 95
4.2.5
Color edge orientation
.............................. 97
4.2.6
Grayscale gradients revisited
......................... 99
4.3
Canny edge operator
...................................... 103
4.3.1
Canny edge detector for grayscale images
..............103
4.3.2
Canny edge detector for color images
.................105
4.4
Implementation
..........................................115
4.5
Other color edge operators
.................................116
5.
Edge-Preserving Smoothing Filters
.........................119
5.1
Kuwahara-type filters
.....................................120
5.1.1
Application to color images
..........................123
5.2
Bilateral filter
............................................126
5.2.1
Domain vs. range filters
.............................128
5.2.2
Bilateral filter with Gaussian kernels
..................131
5.2.3
Application to color images
..........................132
5.2.4
Separable implementation
...........................136
5.2.5
Other implementations and improvements
.............141
5.3 Anisotropie
diffusion filters
................................143
5.3.1
Homogeneous diffusion and the heat equation
..........144
5.3.2
Perona-Malik filter
.................................146
5.3.3
Perona-Malik filter for color images
...................149
5.3.4
Geometry-preserving anisotropic diffusion
.............156
5.3.5
Tschumperlé-Deriche
algorithm
.......................157
5.4
Measuring image quality
..................................161
5.5
Implementation
..........................................164
5.6
Exercises
................................................165
6.
Fourier
Shape Descriptors
..................................169
6.1
2D boundaries in the complex plane
........................169
6.1.1
Parameterized boundary curves
......................169
6.1.2
Discrete 2D boundaries
.............................170
6.2
Discrete Fourier transform
.................................171
6.2.1
Forward transform
..................................173
6.2.2
Inverse Fourier transform (reconstruction)
.............173
6.2.3
Periodicity of the DFT spectrum
.....................177
6.2.4
Truncating the DFT spectrum
.......................177
6.3
Geometric interpretation of Fourier coefficients
...............179
6.3.1
Coefficient
Gq
corresponds to the contour s centroid
.... 180
6.3.2
Coefficient G corresponds to a circle
.................181
6.3.3
Coefficient Gm corresponds to a circle with frequency
m
. 182
6.3.4
Negative frequencies
................................183
6.3.5
Fourier descriptor pairs correspond to ellipses
..........183
6.3.6
Shape reconstruction from truncated Fourier descriptors
. 187
6.3.7
Fourier descriptors from arbitrary polygons
............193
6.4
Effects of geometric transformations
........................195
6.4.1
Translation
........................................197
6.4.2
Scale change
.......................................199
6.4.3
Shape rotation
.....................................199
6.4.4
Shifting the contour start position
....................200
6.4.5
Effects of phase removal
.............................201
6.4.6
Direction of contour traversal
........................203
6.4.7
Reflection (symmetry)
..............................203
6.5
Making Fourier descriptors invariant
........................203
6.5.1
Scale
invariance
....................................204
6.5.2
Start point
invariance
...............................205
6.5.3
Rotation
invariance
...........-......................208
6.5.4
Other approaches
..................................209
6.6
Shape matching with Fourier descriptors
....................214
6.6.1
Magnitude-only matching
...........................214
6.6.2
Complex (phase-preserving) matching
.................218
6.7
Java implementation
......................................219
6.8
Summary and further reading
..............................225
6.9
Exercises
................................................225
7.
SIFT
—
Scale-Invariant Local Features
.......................229
7.1
Interest points at multiple scales
...........................230
7.1.1
The Laplacian-of-Gaussian (LoG) filter
................231
7.1.2
Gaussian scale space
................................237
7.1.3
LoG/DoG scale space
...............................240
7.1.4
Hierarchical scale space
.............................242
7.1.5
Scale space implementation in SIFT
..................248
7.2
Key point selection and refinement
.........................252
7.2.1
Local
extrema
detection
.............................255
7.2.2
Position refinement
.................................257
7.2.3
Suppressing responses to edge-like structures
...........260
7.3
Creating Local Descriptors
................................263
7.3.1
Finding dominant orientations
.......................263
7.3.2
Descriptor formation
................................267
7.4
SIFT algorithm summary
..................................276
7.5
Matching SIFT Features
..................................276
7.5.1
Feature distance and match quality
...................285
7.5.2
Examples
.........................................287
7.6
Efficient feature matching
.................................289
7.7
SIFT implementation in Java
..............................294
7.7.1
SIFT feature extraction
.............................294
7.7.2
SIFT feature matching
..............................295
7.8
Exercises
................................................296
Appendix
A. Mathematical Symbols and Notation
.......................299
B. Vector Algebra and Calculus
...............................305
B.I Vectors
..................................................305
B.I.I Column and row vectors
............................306
B.1.2 Vector length
......................................306
B.2 Matrix multiplication
.....................................306
B.2.1 Scalar multiplication
................................306
B.2.
2
Product of two matrices
.............................307
B.2.3 Matrix-vector products
..............................307
B.3 Vector products
..........................................308
B.3.1 Dot product
.......................................308
B.3.2 Outer product
.....................................309
B.4 Eigenvectors and eigenvalues
...............................309
B.4.1 Eigenvectors of a
2
χ
2
matrix
.......................310
B.5 Parabolic fitting
..........................................311
B.5.1 Fitting a parabolic function to three sample points
.....311
B.5.
2
Parabolic interpolation
..............................313
B.6 Vector fields
.............................................315
8.
6.1
Jacobian
matrix
....................................315
8.6.2
Gradient
..........................................315
8.
6.3
Maximum gradient
direction
.........................316
8.
6.4
Divergence
........................................317
6.б.
5
Laplacian .........................................
317
8.
6.6
The Hessian matrix
.................................318
В.
7
Operations on
multi-
variable, scalar functions (scalar fields)
.... 319
B.7.1 Estimating the derivatives of a discrete function
........319
B.7.2 Taylor series expansion of functions
...................319
B.7.3 Finding the continuous
extrémům
of
a multi-
variable
discrete function
...................................323
C. Statistical Prerequisites
.....................................329
C.I Mean, variance and covariance
.............................329
C.2 Covariance matrices
......................................330
C.2.1 Example
..........................................331
C.3 The Gaussian distribution
.................................332
C.3.1 Maximum likelihood
................................333
C.3.
2
Gaussian mixtures
..................................334
C.3.3 Creating Gaussian noise
.............................335
C.4 Image quality measures
...................................335
D. Gaussian Filters
............................................337
D.I Cascading Gaussian filters
.................................337
D.2 Effects of Gaussian filtering in the frequency domain
..........338
D.3
Lo G-
approximation by the difference of two
Gaussiane (DoG)
. . 339
E. Color Space Transformations
...............................341
E.I RGB/sRGB transformations
...............................341
E.2 CIELAB/CIELUV transformations
.........................342
E.2.1 CIELAB
..........................................343
E.2.
2
CIELUV
..........................................344
Bibliography
....................................................347
Index
...........................................................361
This easy-to-follow textbook is the third of three volumes which provide a modem, algorithmic introduction
to digital ¡mage processing, designed to be used both by learners desiring a firm foundation on which to
build, and practitioners in search of critical analysis and concrete implementations of the most important
techniques. This volume builds upon the introductory material presented in the first two volumes
{Funda-
mental Techniques and Core Algorithms) with additional key concepts and methods in image processing.
Features and topics:
•
Practical examples and carefully constructed chapter-ending exercises drawn from the authors
years of experience teaching this material
•
Real implementations, concise mathematical notation, and precise algorithmic descriptions
designed for programmers and practitioners
•
Easily adaptable Java code and completely worked-out examples for easy inclusion
m
existing (and
rapid prototyping of new) applications
•
Uses imageJ, the image processing system developed, maintained, and freely distributed by the
U.S. National institutes of Health
(NIH)
•
Provides a supplementary website with the complete Java source code, test ¡mages, and
corrections- -www. imagingbook.com
•
Additional presentation tools for instructors including a complete set of figures, tables, and
mathematical elements
This thorough, reader-friendly text will equip undergraduates with a deeper understanding of the topic
and will be invaluable for further developing knowledge via self-study
|
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| isbn | 9781848829183 9781848829190 |
| language | English |
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| spelling | Burger, Wilhelm Verfasser aut Principles of Digital Image Processing Advanced Methods Wilhelm Burger ; Mark J. Burge 1. Aufl. London Springer 2013 XIII, 369 S. Ill., graph. Darst. 235 mm x 178 mm Undergraduate Topics in Computer Science Java Programmiersprache (DE-588)4401313-9 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Bildverarbeitung (DE-588)4006684-8 s Java Programmiersprache (DE-588)4401313-9 s DE-604 Burge, Mark James Verfasser (DE-588)132219336 aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027193962&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027193962&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Burger, Wilhelm Burge, Mark James Principles of Digital Image Processing Advanced Methods Java Programmiersprache (DE-588)4401313-9 gnd Bildverarbeitung (DE-588)4006684-8 gnd |
| subject_GND | (DE-588)4401313-9 (DE-588)4006684-8 (DE-588)4123623-3 |
| title | Principles of Digital Image Processing Advanced Methods |
| title_auth | Principles of Digital Image Processing Advanced Methods |
| title_exact_search | Principles of Digital Image Processing Advanced Methods |
| title_full | Principles of Digital Image Processing Advanced Methods Wilhelm Burger ; Mark J. Burge |
| title_fullStr | Principles of Digital Image Processing Advanced Methods Wilhelm Burger ; Mark J. Burge |
| title_full_unstemmed | Principles of Digital Image Processing Advanced Methods Wilhelm Burger ; Mark J. Burge |
| title_short | Principles of Digital Image Processing |
| title_sort | principles of digital image processing advanced methods |
| title_sub | Advanced Methods |
| topic | Java Programmiersprache (DE-588)4401313-9 gnd Bildverarbeitung (DE-588)4006684-8 gnd |
| topic_facet | Java Programmiersprache Bildverarbeitung Lehrbuch |
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