Digital image processing using MATLAB:
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
New Delhi [u.a.]
Tata McGraw Hill Education
2012
|
Ausgabe: | 2. ed., 7. repr. |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | XVIII, 738 S. Ill., graph. Darst. |
ISBN: | 0070702624 9780070702622 |
Internformat
MARC
LEADER | 00000nam a2200000 c 4500 | ||
---|---|---|---|
001 | BV040876009 | ||
003 | DE-604 | ||
005 | 20130320 | ||
007 | t | ||
008 | 130312s2012 ad|| |||| 00||| eng d | ||
020 | |a 0070702624 |9 0-07-070262-4 | ||
020 | |a 9780070702622 |9 978-0-07-070262-2 | ||
035 | |a (OCoLC)835435995 | ||
035 | |a (DE-599)BSZ358660483 | ||
040 | |a DE-604 |b ger | ||
041 | 0 | |a eng | |
049 | |a DE-739 | ||
084 | |a ST 601 |0 (DE-625)143682: |2 rvk | ||
100 | 1 | |a Gonzalez, Rafael C. |e Verfasser |0 (DE-588)136376770 |4 aut | |
245 | 1 | 0 | |a Digital image processing using MATLAB |c Rafael C. Gonzalez ; Richard E. Woods ; Steven L. Eddins |
250 | |a 2. ed., 7. repr. | ||
264 | 1 | |a New Delhi [u.a.] |b Tata McGraw Hill Education |c 2012 | |
300 | |a XVIII, 738 S. |b Ill., graph. Darst. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
650 | 0 | 7 | |a MATLAB |0 (DE-588)4329066-8 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Bildverarbeitung |0 (DE-588)4006684-8 |2 gnd |9 rswk-swf |
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689 | 0 | 1 | |a MATLAB |0 (DE-588)4329066-8 |D s |
689 | 0 | |8 1\p |5 DE-604 | |
700 | 1 | |a Woods, Richard E. |d 1954- |e Verfasser |0 (DE-588)136376762 |4 aut | |
700 | 1 | |a Eddins, Steven L. |e Verfasser |4 aut | |
856 | 4 | 2 | |m Digitalisierung UB Passau |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025855881&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
999 | |a oai:aleph.bib-bvb.de:BVB01-025855881 | ||
883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk |
Datensatz im Suchindex
_version_ | 1804150156923240449 |
---|---|
adam_text | Contents
Preface
xiii
Acknowledgements
xv
About the Authors
xvii
I Introduction
1
Preview
1
1.1
Background
1
1.2
What Is Digital Image Processing?
2
1.3
Background on
MATLAB
and the Image Processing Toolbox
4
1.4
Areas of Image Processing Covered in the Book
4
1.5
The Book Web Site
6
1.6
Notation
7
1.7
Fundamentals
7
1.7.1
The
MATLAB
Desktop
7
1.7.2
Using the
MATLAB
Editor/Debugger
9
1.7.3
Getting Help
9
1.7.4
Saving and Retrieving Work Session Data
10
1.7.5
Digital Image Representation
11
1.7.6
Image I/O and Display
13
1.7.7
Classes and Image Types
14
1.7.8
M-Function Programming
17
1.8
How References Are Organized in the Book
33
Summary
33
L
Intensity Transformations and
Spatial Filtering
34
Preview
34
2.1
Background
34
2.2
Intensity Transformation Functions
35
2.2.1
Functions imad
j
ust
and stretchlim
36
2.2.2
Logarithmic and Contrast-Stretching Transformations
38
2.2.3
Specifying Arbitrary Intensity Transformations
40
2.2.4
Some Utility M-functions for Intensity Transformations
41
2.3
Histogram Processing and Function Plotting
47
2.3.1
Generating and Plotting Image Histograms
48
2.3.2
Histogram Equalization
53
2.3.3
Histogram Matching (Specification)
56
2.3.4
Function adapthisteq
61
2.4
Spatial Filtering
63
2.4.1
Linear Spatial Filtering
63
vi
H Contents
2.4.2
Nonlinear
Spatial
Filtering
71
2.5
Image Processing
Toolbox
Standard Spatial
Filters
74
2.5.1
Linear
Spatial
Filters
74
2.5.2
Nonlinear
Spatial
Filters
78
2.6
Using Fuzzy Techniques for Intensity Transformations and Spatial
Filtering
82
2.6.1
Background
82
2.6.2
Introduction to Fuzzy Sets
82
2.6.3
Using Fuzzy Sets
87
2.6.4
A Set of Custom Fuzzy M-functions
94
2.6.5
Using Fuzzy Sets for Intensity Transformations
109
2.6.6
Using Fuzzy Sets for Spatial Filtering
112
Summary
117
ó
Filtering in the Frequency Domain
118
Preview
118
3.1
The 2-D Discrete Fourier Transform
118
3.2
Computing and Visualizing the 2-D DFT in
MATLAB
122
3.3
Filtering in the Frequency Domain
126
3.3.1
Fundamentals
127
3.3.2
Basic Steps in DFT Filtering
132
3.3.3
An M-function for Filtering in the Frequency Domain
133
3.4
Obtaining Frequency Domain Filters from Spatial Filters
134
3.5
Generating Filters Directly in the Frequency Domain
139
3.5.1
Creating Meshgrid Arrays for Use in Implementing Filters
in the Frequency Domain
140
3.5.2
Lowpass (Smoothing) Frequency Domain Filters
141
3.5.3
Wireframe and Surface Plotting
144
3.6
Highpass (Sharpening) Frequency Domain Filters
148
3.6.1
A Function for Highpass Filtering
148
3.6.2
High-Frequency Emphasis Filtering
151
3.7
Selective Filtering
153
3.7.1
Bandreject and Bandpass Filters
153
3.7.2
Notchreject and Notchpass Filters
156
Summary
162
Ί
Image Restoration and Reconstruction
163
Preview
163
4.1
A Model of the Image Degradation/Restoration Process
164
4.2
Noise Models
165
4.2.1
Adding Noise to Images with Function imnoise
165
4.2.2
Generating Spatial Random Noise with a Specified
Distribution
166
4.2.3
Periodic Noise
174
M Contents
vii
4.2.4
Estimating Noise Parameters
178
4.3
Restoration in the Presence of Noise Only
—
Spatial Filtering
183
4.3.1
Spatial Noise Filters
183
4.3.2
Adaptive Spatial Filters
187
4.4
Periodic Noise Reduction Using Frequency Domain Filtering
190
4.5
Modeling the Degradation Function
191
4.6
Direct Inverse Filtering
194
4.7
Wiener Filtering
194
4.8
Constrained Least Squares (Regularized) Filtering
198
4.9
Iterative Nonlinear Restoration Using the Lucy-Richardson
Algorithm
200
4.10
Blind Deconvolution
204
4.11
Image Reconstruction from Projections
205
4.11.1
Background
206
4.11.2
Parallel-Beam Projections and the Radon Transform
208
4.11.3
The Fourier Slice Theorem and Filtered Backprojections
211
4.11.4
Filter Implementation
212
4.11.5
Reconstruction Using Fan-Beam Filtered Backprojections
213
4.11.6
Function radon
214
4.11.7
Function iradon
217
4.11.8
Working with Fan-Beam Data
222
Summary
231
J
Geometric Transformations and Image
Registration
232
Preview
232
5.1
Transforming Points
232
5.2
Affine
Transformations
237
5.3
Projective
Transformations
241
5.4
Applying Geometric Transformations to Images
242
5.5
Image Coordinate Systems in
MATLAB
245
5.5.1
Output Image Location
247
5.5.2
Controlling the Output Grid
251
5.6
Image Interpolation
253
5.6.1
Interpolation in Two Dimensions
256
5.6.2
Comparing Interpolation Methods
256
5.7
Image Registration
259
5.7.1
Registration Process
260
5.7.2
Manual Feature Selection and Matching Using cpselect
260
5.7.3
Inferring Transformation Parameters Using cp2tf
orm
261
5.7.4
Visualizing Aligned Images
261
5.7.5
Area-Based Registration
265
5.7.6
Automatic Feature-Based Registration
270
Summary
271
viii
■ Contents
0
Color Image
Processing
272
Preview
272
6.1
Color Image Representation in
MATLAB
272
6.1.1
RGB Images
272
6.1.2
Indexed Images
275
6.1.3
Functions for Manipulating RGB and Indexed Images
277
6.2
Converting Between Color Spaces
282
6.2.1
NTSC Color Space
282
6.2.2
The YCbCr Color Space
283
6.2.3
The
HSV
Color Space
283
6.2.4
The CMY and CMYK Color Spaces
284
6.2.5
The HSI Color Space
285
6.2.6
Device-Independent Color Spaces
294
6.3
The Basics of Color Image Processing
303
6.4
Color Transformations
304
6.5
Spatial Filtering of Color Images
314
6.5.1
Color Image Smoothing
314
6.5.2
Color Image Sharpening
319
6.6
Working Directly in RGB Vector Space
320
6.6.1
Color Edge Detection Using the Gradient
320
6.6.2
Image Segmentation in RGB Vector Space
326
Summary
330
1
Wavelets
331
Preview
331
7.1
Background
331
7.2
The Fast Wavelet Transform
334
7.2.1
FWTs Using the Wavelet Toolbox
335
7.2.2
FWTs without the Wavelet Toolbox
341
7.3
Working with Wavelet Decomposition Structures
350
7.3.1
Editing Wavelet Decomposition Coefficients without the
Wavelet Toolbox
353
7.3.2
Displaying Wavelet Decomposition Coefficients
358
7.4
The Inverse Fast Wavelet Transform
362
7.5
Wavelets in Image Processing
368
Summary
373
0
Image Compression
374
Preview
374
8.1
Background
375
8.2
Coding Redundancy
378
8.2.1
Huffman Codes
381
8.2.2
Huffman Encoding
387
Contents ix
8.2.3 Huffman Decoding 393
8.3
Spatial
Redundancy
400
8.4 Irrelevant Information 407
8.5 JPEG
Compression
410
8.5.1 JPEG 410
8.5.2 JPEG 2000 418
8.6 Video
Compression
426
8.6.1
MATLAB
Image
Sequences and Movies
427
8.6.2
Temporal Redundancy and Motion Compensation
430
Summary
439
/
Morphological Image Processing
440
Preview
440
9.1
Preliminaries
441
9.1.1
Some Basic Concepts from Set Theory
441
9.1.2
Binary Images, Sets, and Logical Operators
443
9.2
Dilation and Erosion
444
9.2.1
Dilation
444
9.2.2
Structuring Element Decomposition
447
9.2.3
The
strel
Function
448
9.2.4
Erosion
451
9.3
Combining Dilation and Erosion
454
9.3.1
Opening and Closing
454
9.3.2
The Hit-or-Miss Transformation
457
9.3.3
Using Lookup Tables
460
9.3.4
Function bwmorph
465
9.4
Labeling Connected Components
468
9.5
Morphological Reconstruction
472
9.5.1
Opening by Reconstruction
472
9.5.2
Filling Holes
474
9.5.3
Clearing Border Objects
475
9.6
Gray-Scale Morphology
475
9.6.1
Dilation and Erosion
475
9.6.2
Opening and Closing
478
9.6.3
Reconstruction
484
Summary
488
IU Image Segmentation
489
Preview
489
10.1
Point, Line, and Edge Detection
490
10.1.1
Point Detection
490
10.1.2
Line Detection
492
10.1.3
Edge Detection Using Function edge
495
10.2
Line Detection Using the Hough Transform
503
10.2.1
Background
505
Contents
10.2.2
Toolbox Hough Functions
506
10.3
Thresholding
511
10.3.1
Foundation
511
10.3.2
Basic Global Thresholding
513
10.3.3
Optimum Global Thresholding Using Otsu s Method
515
10.3.4
Using Image Smoothing to Improve Global Thresholding
519
10.3.5
Using Edges to Improve Global Thresholding
521
10.3.6
Variable Thresholding Based on Local Statistics
525
10.3.7
Image Thresholding Using Moving Averages
529
10.4
Region-Based Segmentation
532
10.4.1
Basic Formulation
532
10.4.2
Region Growing
532
10.4.3
Region Splitting and Merging
536
10.5
Segmentation Using the Watershed Transform
542
10.5.1
Watershed Segmentation Using the Distance Transform
543
10.5.2
Watershed Segmentation Using Gradients
545
10.5.3
Marker-Controlled Watershed Segmentation
547
Summary
550
Representation and Description
551
Preview
551
11.1
Background
551
11.1.1
Functions for Extracting Regions and Their Boundaries
552
11.1.2
Some Additional
MATLAB
and Toolbox Functions Used
in This Chapter
557
11.1.3
Some Basic Utility M-Functions
558
11.2
Representation
560
11.2.1
Chain Codes
560
11.2.2
Polygonal Approximations Using Minimum-Perimeter
Polygons
564
11.2.3
Signatures
573
11.2.4
Boundary Segments
576
11.2.5
Skeletons
577
11.3
Boundary Descriptors
579
11.3.1
Some Simple Descriptors
579
11.3.2
Shape Numbers
580
11.3.3
Fourier Descriptors
581
11.3.4
Statistical Moments
586
11.3.5
Corners
587
11.4
Regional Descriptors
595
11.4.1
Function regionprops
596
11.4.2
Texture
598
11.4.3
Moment Invariants
610
11.5
Using Principal Components for Description
615
Summary
626
-!<
Contents
xi
АррбПиІХ
A M-Function Summary
628
Appendix
D ICE
and
MATLAB
Graphical User
Interfaces
643
Appendix I Additional Custom
M-functions
669
Bibliography
725
Index
729
|
any_adam_object | 1 |
author | Gonzalez, Rafael C. Woods, Richard E. 1954- Eddins, Steven L. |
author_GND | (DE-588)136376770 (DE-588)136376762 |
author_facet | Gonzalez, Rafael C. Woods, Richard E. 1954- Eddins, Steven L. |
author_role | aut aut aut |
author_sort | Gonzalez, Rafael C. |
author_variant | r c g rc rcg r e w re rew s l e sl sle |
building | Verbundindex |
bvnumber | BV040876009 |
classification_rvk | ST 601 |
ctrlnum | (OCoLC)835435995 (DE-599)BSZ358660483 |
discipline | Informatik |
edition | 2. ed., 7. repr. |
format | Book |
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id | DE-604.BV040876009 |
illustrated | Illustrated |
indexdate | 2024-07-10T00:34:27Z |
institution | BVB |
isbn | 0070702624 9780070702622 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025855881 |
oclc_num | 835435995 |
open_access_boolean | |
owner | DE-739 |
owner_facet | DE-739 |
physical | XVIII, 738 S. Ill., graph. Darst. |
publishDate | 2012 |
publishDateSearch | 2012 |
publishDateSort | 2012 |
publisher | Tata McGraw Hill Education |
record_format | marc |
spelling | Gonzalez, Rafael C. Verfasser (DE-588)136376770 aut Digital image processing using MATLAB Rafael C. Gonzalez ; Richard E. Woods ; Steven L. Eddins 2. ed., 7. repr. New Delhi [u.a.] Tata McGraw Hill Education 2012 XVIII, 738 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier MATLAB (DE-588)4329066-8 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 s MATLAB (DE-588)4329066-8 s 1\p DE-604 Woods, Richard E. 1954- Verfasser (DE-588)136376762 aut Eddins, Steven L. Verfasser aut Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025855881&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Gonzalez, Rafael C. Woods, Richard E. 1954- Eddins, Steven L. Digital image processing using MATLAB MATLAB (DE-588)4329066-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd |
subject_GND | (DE-588)4329066-8 (DE-588)4006684-8 |
title | Digital image processing using MATLAB |
title_auth | Digital image processing using MATLAB |
title_exact_search | Digital image processing using MATLAB |
title_full | Digital image processing using MATLAB Rafael C. Gonzalez ; Richard E. Woods ; Steven L. Eddins |
title_fullStr | Digital image processing using MATLAB Rafael C. Gonzalez ; Richard E. Woods ; Steven L. Eddins |
title_full_unstemmed | Digital image processing using MATLAB Rafael C. Gonzalez ; Richard E. Woods ; Steven L. Eddins |
title_short | Digital image processing using MATLAB |
title_sort | digital image processing using matlab |
topic | MATLAB (DE-588)4329066-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd |
topic_facet | MATLAB Bildverarbeitung |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025855881&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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