Fundamentals of Digital Image Processing,9780133361650

Fundamentals of Digital Image Processing

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Edition: 1st
ISBN13: 9780133361650
ISBN10: 0133361659
Format: Paperback
Pub. Date: 1988-09-23
Publisher(s): Pearson
List Price: $246.64

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Summary

Presents a thorough overview of the major topics of digital image processing, beginning with the basic mathematical tools needed for the subject. Includes a comprehensive chapter on stochastic models for digital image processing.Covers aspects of image representation including luminance, color, spatial and temporal properties of vision, and digitization. Explores various image processing techniques. Discusses algorithm development (software/firmware) for image transforms, enhancement, reconstruction, and image coding.

Table of Contents

Preface xix
Acknowledgments xxi
Introduction
1(10)
Digital Image Processing: Problems and Applications
1(3)
Image Representation and Modeling
4(2)
Image Enhancement
6(1)
Image Restoration
7(1)
Image Analysis
7(1)
Image Reconstruction from Projections
8(1)
Image Data Compression
9(1)
Bibliography
10(1)
Two-Dimensional Systems and Mathematical Preliminaries
11(38)
Introduction
11(1)
Notation and Definitions
11(2)
Linear Systems and Shift Invariance
13(2)
The Fourier Transform
15(5)
Properties of the Fourier Transform
16(2)
Fourier Transform of Sequences (Fourier Series)
18(2)
The Z-Transform or Laurent Series
20(1)
Causality and Stability
21(1)
Optical and Modulation Transfer Functions
21(1)
Matrix Theory Results
22(6)
Vectors and Matrices
22(1)
Row and Column Ordering
23(2)
Transposition and Conjugation Rules
25(1)
Toeplitz and Circulant Matrices
25(1)
Orthogonal and Unitary Matrices
26(1)
Positive Definiteness and Quadratic Forms
27(1)
Diagonal Forms
27(1)
Block Matrices and Kronecker Products
28(3)
Block Matrices
28(2)
Kronecker Products
30(1)
Separable Operations
31(1)
Random Signals
31(4)
Definitions
31(1)
Gaussian or Normal Distribution
32(1)
Gaussian Random Processes
32(1)
Stationary Processes
32(1)
Markov Processes
33(1)
Orthogonality and Independence
34(1)
The Karhunen Loeve (KL) Transform
34(1)
Discrete Random Fields
35(2)
Definitions
35(1)
Separable and Isotropic Covariance Functions
36(1)
The Spectral Density Function
37(2)
Properties of the SDF
38(1)
Some Results from Estimation Theory
39(2)
Mean Square Estimates
40(1)
The Orthogonality Principle
40(1)
Some Results from Information Theory
41(8)
Information
42(1)
Entropy
42(1)
The Rate Distortion Function
43(1)
Problems
44(3)
Bibliography
47(2)
Image Perception
49(31)
Introduction
49(1)
Light, Luminance, Brightness, and Contrast
49(5)
Simultaneous Contrast
51(2)
Mach Bands
53(1)
MTF of the Visual System
54(1)
The Visibility Function
55(1)
Monochrome Vision Models
56(1)
Image Fidelity Criteria
57(3)
Color Representation
60(2)
Color Matching and Reproduction
62(4)
Laws of Color Matching
63(2)
Chromaticity Diagram
65(1)
Color Coordinate Systems
66(5)
Color Difference Measures
71(2)
Color Vision Model
73(2)
Temporal Properties of Vision
75(5)
Bloch's Law
75(1)
Critical Fusion Frequency (CFF)
75(1)
Spatial versus Temporal Effects
75(1)
Problems
76(2)
Bibliography
78(2)
Image Sampling and Quantization
80(52)
Introduction
80(4)
Image Scanning
80(1)
Television Standards
81(2)
Image Display and Recording
83(1)
Two-Dimensional Sampling Theory
84(5)
Bandlimited Images
84(1)
Sampling Versus Replication
85(1)
Reconstruction of the Image from Its Samples
85(2)
Nyquist Rate, Aliasing, and Foldover Frequencies
87(1)
Sampling Theorem
88(1)
Remarks
89(1)
Extensions of Sampling Theory
89(4)
Sampling Random Fields
90(1)
Sampling Theorem for Random Fields
90(1)
Remarks
90(1)
Nonrectangular Grid Sampling and Interlacing
91(1)
Hexagonal Sampling
92(1)
Optimal Sampling
92(1)
Practical Limitations in Sampling and Reconstruction
93(6)
Sampling Aperture
93(1)
Display Aperture/Interpolation Function
94(4)
Lagrange Interpolation
98(1)
Moire Effect and Flat Field Response
99(1)
Image Quantization
99(2)
The Optimum Mean Square or Lloyd-Max Quantizer
101(12)
The Uniform Optimal Quantizer
103(1)
Properties of the Optimum Mean Square Quantizer
103(9)
Proofs
112(1)
A Compandor Design
113(2)
Remarks
114(1)
The Optimum Mean Square Uniform Quantizer for Nonuniform Densities
115(1)
Examples, Comparison, and Practical Limitations
115(3)
Analytic Models for Practical Quantizers
118(1)
Quantization of Complex Gaussian Random Variables
119(1)
Visual Quantization
119(13)
Contrast Quantization
120(1)
Pseudorandom Noise Quantization
120(1)
Halftone Image Generation
121(1)
Color Quantization
122(2)
Problems
124(4)
Bibliography
128(4)
Image Transforms
132(57)
Introduction
132(2)
Two-Dimensional Orthogonal and Unitary Transforms
134(4)
Separable Unitary Transforms
134(1)
Basis Images
135(2)
Kronecker Products and Dimensionality
137(1)
Dimensionality of Image Transforms
138(1)
Transform Frequency
138(1)
Optimum Transform
138(1)
Properties of Unitary Transforms
138(3)
Energy Conservation and Rotation
138(1)
Energy Compaction and Variances of Transform Coefficients
139(1)
Decorrelation
140(1)
Other Properties
140(1)
The One-Dimensional Discrete Fourier Transform (DFT)
141(4)
Properties of the DFT/Unitary DFT
141(4)
The Two-Dimensional DFT
145(5)
Properties of the Two-Dimensional DFT
147(3)
The Cosine Transform
150(4)
Properties of the Cosine Transform
151(3)
The Sine Transform
154(1)
Properties of the Sine Transform
154(1)
The Hadamard Transform
155(4)
Properties of the Hadamard Transform
157(2)
The Haar Transform
159(2)
Properties of the Haar Transform
161(1)
The Slant Transform
161(2)
Properties of the Slant Transform
162(1)
The KL Transform
163(12)
KL Transform of Images
164(1)
Properties of the KL Transform
165(10)
A Sinusoidal Family of Unitary Transforms
175(1)
Approximation to the KL Transform
176(1)
Outer Product Expansion and Singular Value Decomposition
176(4)
Properties of the SVD Transform
177(3)
Summary
180(9)
Problems
180(5)
Bibliography
185(4)
Image Representation by Stochastic Models
189(44)
Introduction
189(1)
Covariance Models
189(1)
Linear System Models
189(1)
One-Dimensional Causal Models
190(6)
Autoregressive (AR) Models
190(1)
Properties of AR Models
191(2)
Application of AR Models in Image Processing
193(1)
Moving Average (MA) Representations
194(1)
Autoregressive Moving Average (ARMA) Representations
195(1)
State Variable Models
195(1)
Image Scanning Models
196(1)
One-Dimensional Spectral Factorization
196(2)
Rational SDFs
197(1)
Remarks
198(1)
AR Models, Spectral Factorization, and Levinson Algorithm
198(2)
The Levinson-Durbin Algorithm
198(2)
Noncausal Representations
200(4)
Remarks
201(1)
Noncausal MVRs for Autoregressive Sequences
201(1)
A Fast KL Transform
202(2)
Optimum Interpolation of Images
204(1)
Linear Prediction in Two Dimensions
204(9)
Causal Prediction
205(1)
Semicausal Prediction
206(1)
Noncausal Prediction
206(1)
Minimum Variance Prediction
206(1)
Stochastic Representation of Random Fields
207(1)
Finite-Order MVRs
208(1)
Remarks
209(3)
Stability of Two-Dimensional Systems
212(1)
Two-Dimensional Spectral Factorization and Spectral Estimation Via Prediction Models
213(6)
Separable Models
214(1)
Realization of Noncausal MVRs
215(1)
Realization of Causal and Semicausal MVRs
216(1)
Realization via Orthogonality Condition
216(3)
Spectral Factorization via the Wiener-Doob Homomorphic Transformation
219(4)
Causal MVRs
220(1)
Semicausal WNDRs
220(2)
Semicausal MVRs
222(1)
Remarks and Examples
222(1)
Image Decomposition, Fast KL Transforms, and Stochastic Decoupling
223(3)
Periodic Random Fields
223(1)
Noncausal Models and Fast KL Transforms
224(1)
Semicausal Models and Stochastic Decoupling
225(1)
Summary
226(7)
Problems
227(3)
Bibliography
230(3)
Image Enhancement
233(34)
Introduction
233(2)
Point Operations
235(6)
Contrast Stretching
235(1)
Clipping and Thresholding
235(3)
Digital Negative
238(1)
Intensity Level Slicing
238(1)
Bit Extraction
239(1)
Range Compression
240(1)
Image Subtraction and Change Detection
240(1)
Histogram Modeling
241(3)
Histogram Equalization
241(1)
Histogram Modification
242(1)
Histogram Specification
243(1)
Spatial Operations
244(12)
Spatial Averaging and Spatial Low-pass Filtering
244(1)
Directional Smoothing
245(1)
Median Filtering
246(3)
Other Smoothing Techniques
249(1)
Unsharp Masking and Crispening
249(1)
Spatial Low-pass, High-pass and Band-pass Filtering
250(2)
Inverse Contrast Ratio Mapping and Statistical Scaling
252(1)
Magnification and Interpolation (Zooming)
253(1)
Replication
253(1)
Linear Interpolation
253(3)
Transform Operations
256(4)
Generalized Linear Filtering
256(2)
Root Filtering
258(1)
Generalized Cepstrum and Homomorphic Filtering
259(1)
Multispectral Image Enhancement
260(2)
Intensity Ratios
260(1)
Log-Ratios
261(1)
Principal Components
261(1)
False Color and Pseudocolor
262(1)
Color Image Enhancement
262(1)
Summary
263(4)
Problems
263(2)
Bibliography
265(2)
Image Filtering and Restoration
267(75)
Introduction
267(1)
Image Observation Models
268(7)
Image Formation Models
269(4)
Detector and Recorder Models
273(1)
Noise Models
273(2)
Sampled Image Observation Models
275(1)
Inverse and Wiener Filtering
275(9)
Inverse Filter
275(1)
Pseudoinverse Filter
276(1)
The Wiener Filter
276(3)
Remarks
279(5)
Finite Impulse Response (FIR) Wiener Filters
284(6)
Filter Design
284(1)
Remarks
285(2)
Spatially Varying FIR Filters
287(3)
Other Fourier Domain Filters
290(2)
Geometric Mean Filter
291(1)
Nonlinear Filters
291(1)
Filtering Using Image Transforms
292(3)
Wiener Filtering
292(1)
Remarks
293(1)
Generalized Wiener Filtering
293(2)
Filtering by Fast Decompositions
295(1)
Smoothing Splines and Interpolation
295(2)
Remarks
297(1)
Least Squares Filters
297(2)
Constrained Least Squares Restoration
297(1)
Remarks
298(1)
Generalized Inverse, SVD, and Iterative Methods
299(5)
The Pseudoinverse
299(1)
Minimum Norm Least Squares (MNLS) Solution and the Generalized Inverse
300(1)
One-step Gradient Methods
301(1)
Van Cittert Filter
301(1)
The Conjugate Gradient Method
302(1)
Separable Point Spread Functions
303(1)
Recursive Filtering For State Variable Systems
304(3)
Kalman Filtering
304(3)
Remarks
307(1)
Casual Models and Recursive Filtering
307(4)
A Vector Recursive Filter
308(2)
Stationary Models
310(1)
Steady-State Filter
310(1)
A Two-Stage Recursive Filter
310(1)
A Reduced Update Filter
310(1)
Remarks
311(1)
Semicausal Models and Semirecursive Filtering
311(2)
Filter Formulation
312(1)
Digital Processing of Speckle Images
313(3)
Speckle Representation
313(2)
Speckle Reduction: N-Look Method
315(1)
Spatial Averaging of Speckle
315(1)
Homomorphic Filtering
315(1)
Maximum Entropy Restoration
316(3)
Distribution-Entropy Restoration
317(1)
Log-Entropy Restoration
318(1)
Bayesian Methods
319(1)
Remarks
320(1)
Coordinate Transformation and Geometric Correction
320(2)
Blind Deconvolution
322(1)
Extrapolation of Bandlimited Signals
323(7)
Analytic Continuation
323(1)
Super-resolution
323(1)
Extrapolation Via Prolate Spheroidal Wave Functions (PSWFs)
324(1)
Extrapolation by Error Energy Reduction
324(2)
Extrapolation of Sampled Signals
326(1)
Minimum Norm Least Squares (MNLS) Extrapolation
326(1)
Iterative Algorithms
327(1)
Discrete Prolate Spheroidal Sequences (DPSS)
327(1)
Mean Square Extrapolation
328(1)
Generalization to Two Dimensions
328(2)
Summary
330(12)
Problems
331(4)
Bibliography
335(7)
Image Analysis and Computer Vision
342(89)
Introduction
342(2)
Spatial Feature Extraction
344(2)
Amplitude Features
344(1)
Histogram Features
344(2)
Transform Features
346(1)
Edge Detection
347(10)
Gradient Operators
348(2)
Compass Operators
350(1)
Laplace Operators and Zero Crossings
351(2)
Stochastic Gradients
353(2)
Performance of Edge Detection Operators
355(1)
Line and Spot Detection
356(1)
Boundary Extraction
357(5)
Connectivity
357(1)
Contour Following
358(1)
Edge Linking and Heuristic Graph Searching
358(1)
Dynamic Programming
359(3)
Hough Transform
362(1)
Boundary Representation
362(13)
Chain Codes
363(1)
Fitting Line Segments
364(1)
B-Spline Representation
364(6)
Fourier Descriptors
370(4)
Autoregressive Models
374(1)
Region Representation
375(2)
Run-length Codes
375(1)
Quad-Trees
375(1)
Projections
376(1)
Moment Representation
377(4)
Definitions
377(1)
Moment Representation Theorem
378(1)
Moment Matching
378(1)
Orthogonal Moments
379(1)
Moment Invariants
380(1)
Applications of Moment Invariants
381(1)
Structure
381(9)
Medial Axis Transform
381(3)
Morphological Processing
384(3)
Morphological Transforms
387(3)
Shape Feature
390(4)
Geometry Features
391(1)
Moment-Based Features
392(2)
Texture
394(6)
Statistical Approaches
394(4)
Structural Approaches
398(1)
Other Approaches
399(1)
Scene Matching and Detection
400(7)
Image Subtraction
400(1)
Template Matching and Area Correlation
400(3)
Matched Filtering
403(1)
Direct Search Methods
404(3)
Image Segmentation
407(7)
Amplitude Thresholding or Window Slicing
407(2)
Component Labeling
409(2)
Boundary-based Approaches
411(1)
Region-based Approaches and Clustering
412(1)
Template Matching
413(1)
Texture Segmentation
413(1)
Classification Techniques
414(7)
Supervised Learning
414(4)
Nonsupervised Learning or Clustering
418(3)
Image Understanding
421(10)
Problems
422(3)
Bibliography
425(6)
Image Reconstruction From Projections
431(45)
Introduction
431(3)
Transmission Tomography
431(1)
Reflection Tomography
432(1)
Emission Tomography
433(1)
Magnetic Resonance Imaging
434(1)
Projection-based Image Processing
434(1)
The Radon Transform
434(5)
Definition
434(2)
Notation
436(1)
Properties of the Radon Transform
437(2)
The Back-projection Operator
439(3)
Definition
439(1)
Remarks
440(2)
The Projection Theorem
442(2)
Remarks
443(1)
The Inverse Radon Transform
444(4)
Remarks
445(1)
Convolution Back-projection Method
446(1)
Filter Back-projection Method
446(1)
Two-Dimensional Filtering via the Radon Transform
447(1)
Convolution/Filter Back-projection Algorithms: Digital Implementation
448(4)
Sampling Considerations
448(1)
Choice of Filters
448(2)
Convolution Back-projection Algorithm
450(1)
Filter Back-projection Algorithm
451(1)
Reconstruction Using a Parallel Pipeline Processor
452(1)
Radon Transform of Random Fields
452(6)
A Unitary Transform R
452(4)
Radon Transform Properties for Random Fields
456(1)
Projection Theorem for Random Fields
457(1)
Reconstruction from Blurred Noisy Projections
458(4)
Measurement Model
458(1)
The Optimum Mean Square Filter
458(1)
Remarks
458(4)
Fourier Reconstruction
462(2)
Algorithm
462(1)
Reconstruction of Magnetic Resonance Images
463(1)
Fan-Beam Reconstruction
464(1)
Algebraic Methods
465(3)
The Reconstruction Problem as a Set of Linear Equations
465(1)
Algebraic Reconstruction Techniques
466(2)
Three-Dimensional Tomography
468(2)
Three-Dimensional Reconstruction Algorithms
469(1)
Summary
470(6)
Problems
470(3)
Bibliography
473(3)
Image Data Compression
476(90)
Introduction
476(3)
Image Raw Data Rates
476(1)
Data Compression versus Bandwidth Compression
477(1)
Information Rates
477(2)
Subsampling, Coarse Quantization, Frame Repetition, and Interlacing
479(1)
Pixel Coding
479(4)
PCM
480(1)
Entropy Coding
480(1)
Run-Length Coding
481(2)
Bit-Plane Encoding
483(1)
Predictive Techniques
483(15)
Basic Principle
483(1)
Feedback versus Feedforward Prediction
484(1)
Distortionless Predictive Coding
485(1)
Performance Analysis of DPCM
486(2)
Delta Modulation
488(2)
Line-by-Line DPCM
490(1)
Two-Dimensional DPCM
491(2)
Performance Comparisons
493(1)
Remarks
494(1)
Adaptive Techniques
495(2)
Other Methods
497(1)
Transform Coding Theory
498(6)
The Optimum Transform Coder
498(1)
Proofs
499(2)
Remarks
501(1)
Bit Allocation and Rate-Distortion Characteristics
501(3)
Transform Coding of Images
504(14)
Two-Dimensional Coding Algorithm
504(3)
Transform Coding Performances Trade-offs and Examples
507(1)
Zonal versus Threshold Coding
508(2)
Fast KL Transform Coding
510(2)
Remarks
512(1)
Two-Source Coding
513(2)
Transform Coding under Visual Criterion
515(1)
Adaptive Transform Coding
515(1)
Summary of Transform Coding
516(2)
Hybrid Coding and Vector DPCM
518(3)
Basic Idea
518(2)
Adaptive Hybrid Coding
520(1)
Hybrid Coding Conclusions
521(1)
Interframe Coding
521(11)
Frame Repetition
521(1)
Resolution Exchange
521(1)
Conditional Replenishment
522(1)
Adaptive Predictive Coding
522(2)
Predictive Coding with Motion Compensation
524(3)
Interframe Hybrid Coding
527(2)
Three-Dimensional Transform Coding
529(3)
Image Coding in the Presence of Channel Errors
532(8)
The Optimum Mean Square Decoder
532(1)
The Optimum Encoding Rule
533(1)
Optimization of PCM Transmission
534(2)
Channel Error Effects in DPCM
536(1)
Optimization of Transform Coding
537(3)
Coding of Two Tone Images
540(13)
Run-length Coding
540(6)
White Block Skipping
546(1)
Prediction Differential Quantization
547(1)
Relative Address Coding
547(1)
CCITT Modified Relative Element Address Designate Coding
548(3)
Predictive Coding
551(1)
Adaptive Predictors
552(1)
Comparison of Algorithms
553(1)
Other Methods
553(1)
Color and Multispectral Image Coding
553(4)
Summary
557(9)
Problems
557(4)
Bibliography
561(5)
Index 566

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