Multidimensional Signal, Image, and Video Processing and Coding

✍ Scribed by John W. Woods

• Publisher: Academic Press
• Year: 2006
• Tongue: English
• Leaves: 512
• Edition: HAR/CDR
• Category: Library

✦ Synopsis

Digital images have become mainstream of late notably within HDTV, cell phones, personal cameras, and many medical applications. The processing of digital images and video includes adjusting illumination, manufacturing enlargements/reductions, and creating contrast. This development has made it possible to take long forgotten, badly damaged photos and make them new again with image estimation. It can also help snapshot photographers with image restoration, a method of reducing the influence of an unsteady hand.

Dr. Woods has constructed a book for professionals and graduate students that will give them the thorough understanding of image and video processing that they need in order to contribute to this hot technology's future advances. Examples and problems at the end of each chapter help the reader digest what has just been read. Forged from a theoretical base, this exceptional book develops into an essential guide to hands-on endeavors in signal processing.

• Overflowing with over 150 digital images
• Brimming with productive examples and challenging problems
• Written by celebrated MIT graduate who has authored four other exceptional books

✦ Table of Contents

Front cover
Title page
Date-line
Contents
Preface
1 Two-Dimensional Signals and Systems
1.1 Two-Dimensional Signals
1.1.1 Separable Signals
1.1.2 Periodic signals
1.1.3 2-D Discrete-Space Systems
1.1.4 Two-Dimensional Convolution
1.1.5 Stability of 2-D Systems
1.2 2-D Discrete-Space Fourier Transform
1.2.1 Inverse 2-D Fourier Transform
1.2.2 Fourier Transform of 2-D or Spatial Convolution
1.2.3 Symmetry Properties of Fourier Transform
1.2.4 Continuous-Space Fourier Transform
1.3 Conclusions
1.4 Problems
References
2 Sampling in Two Dimensions
2.1 Sampling Theorem—Rectangular Case
2.1.1 Reconstruction Formula
2.1.2 Ideal Rectangular Sampling
2.2 Sampling Theorem—General Regular Case
2.2.1 Hexagonal Reconstruction Formula
2.3 Change of Sample Rate
2.3.1 Downsampling by Integers $M_1 \times M_2$
2.3.2 Ideal Decimation
2.3.3 Upsampling by Integers $L_1 \times L_2$
2.3.4 Ideal Interpolation
2.4 Sample-Rate Change—General Case
2.4.1 General Downsampling
2.5 Conclusions
2.6 Problems
References
3 Two-Dimensional Systems and Z-Transforms
3.1 Linear Spatial or 2-D Systems
3.2 Z-Transforms
3.3 Regions of Convergence
3.3.1 More General Case
3.4 Some Z-Transform Properties
3.4.1 Linear Mapping of Variables
3.4.2 Inverse Z-Transform
3.5 2-D Filter Stability
3.5.1 First-Quadrant Support
3.5.2 Second-Quadrant Support
3.5.3 Root Maps
3.5.4 Stability Criteria for NSHP Support Filters
3.6 Conclusions
3.7 Problems
References
4 Two-Dimensional Discrete Transforms
4.1 Discrete Fourier Series
4.1.1 Properties of the DFS Transform
4.1.2 Periodic Convolution
4.1.3 Shifting or Delay Property
4.2 Discrete Fourier Transform
4.2.1 DFT Properties
4.2.2 Relation of DFT to Fourier Transform
4.2.3 Effect of Sampling in Frequency
4.2.4 Interpolating the DFT
4.3 2-D Discrete Cosine Transform
4.3.1 Review of 1-D DCT
4.3.2 Some 1-D DCT Properties
4.3.3 Symmetric Extension in 2-D DCT
4.4 Subband/Wavelet Transform (SWT)
4.4.1 Ideal Filter Case
4.4.2 1-D SWT with Finite-Order Filter
4.4.3 2-D SWT with FIR Filters
4.4.4 Relation of SWT to DCT
4.4.5 Relation of SWT to Wavelets
4.5 Fast Transform Algorithms
4.5.1 Fast DFT Algorithm
4.5.2 Fast DCT Methods
4.6 Sectioned Convolution Methods
4.7 Conclusions
4.8 Problems
References
5 Two-Dimensional Filter Design
5.1 FIR Filter Design
5.1.1 FIR Window Function Design
5.1.2 Design by Transformation of 1-D Filter
5.1.3 Projection-Onto-Convex-Sets Method
5.2 IIR Filter Design
5.2.1 2-D Recursive Filter Design
5.2.2 Fully Recursive Filter Design
5.3 Subband/Wavelet Filter Design
5.3.1 Wavelet (Biorthogonal) Filter Design Method
5.4 Conclusions
5.5 Problems
References
6 Introductory Image Processing
6.1 Light and Luminance
6.2 Still Image Visual Properties
6.2.1 Weber's Law
6.2.2 Contrast Sensitivity Function
6.2.3 Local Contrast Adaptation
6.3 Time-Variant Human Visual System Properties
6.4 Image Sensors
6.4.1 Electronic
6.4.2 Film
6.5 Image and Video Display
6.5.1 Gamma
6.6 Simple Image Processing Filters
6.6.1 Box Filter
6.6.2 Gaussian Filter
6.6.3 Prewitt Operator
6.6.4 Sobel Operator
6.6.5 Laplacian Filter
6.7 Conclusions
6.8 Problems
References
7 Image Estimation and Restoration
7.1 2-D Random Fields
7.1.1 Filtering a 2-D Random Field
7.1.2 Autoregressive Random Signal Models
7.2 Estimation for Random Fields
7.2.1 Infinite Observation Domain
7.3 2-D Recursive Estimation
7.3.1 1-D Kalman Filter
7.3.2 2-D Kalman Filtering
7.3.3 Reduced Update Kalman Filter
7.3.4 Approximate RUKF
7.3.5 Steady-State RUKF
7.3.6 LSI Estimation and Restoration Examples with RUKF
7.4 Inhomogeneous Gaussian Estimation
7.4.1 Inhomogeneous Estimation with RUKF
7.5 Estimation in the Subband/Wavelet Domain
7.6 Bayesian and MAP Estimation
7.6.1 Gauss Markov Image Models
7.6.2 Simulated Annealing
7.7 Image Identification and Restoration
7.7.1 Expectation-Maximization Algorithm Approach
7.7.2 EM Method in the Subband/Wavelet Domain
7.8 Color Image Processing
7.9 Conclusions
7.10 Problems
References
8 Digital Image Compression
8.1 Introduction
8.2 Transformation
8.2.1 DCT
8.2.2 SWT
8.2.3 DPCM
8.3 Quantization
8.3.1 Uniform Quantization
8.3.2 Optimal MSE Quantization
8.3.3 Vector Quantization
8.3.4 LBG Algorithm [7]
8.4 Entropy Coding
8.4.1 Huffman Coding
8.4.2 Arithmetic Coding
8.4.3 ECSQ and ECVQ
8.5 DCT Coder
8.6 SWT Coder
8.6.1 Multiresolution SWT Coding
8.6.2 Nondyadic SWT Decompositions
8.6.3 Fully Embedded SWT Coders
8.6.4 Embedded Zero-Tree Wavelet (EZW) Coder
8.6.5 Set Partitioning in Hierarchical Trees (SPIHT) Coder
8.6.6 Embedded Zero Block Coder (EZBC)
8.7 JPEG 2000
8.8 Color Image Coding
8.8.1 Scalable Coder Results Comparison
8.9 Robustness Considerations
8.10 Conclusions
8.11 Problems
References
9 Three-Dimensional and Spatiotemporal Processing
9.1 3-D Signals and Systems
9.1.1 Properties of 3-D Fourier Transform
9.1.2 3-D Filters
9.2 3-D Sampling and Reconstruction
9.2.1 General 3-D Sampling
9.3 Spatiotemporal Signal Processing
9.3.1 Spatiotemporal Sampling
9.3.2 Spatiotemporal Filters
9.3.3 Intraframe Filtering
9.3.4 Intraframe Wiener Filter
9.3.5 Interframe Filtering
9.3.6 Interframe Wiener Filter
9.4 Spatiotemporal Markov Models
9.4.1 Causal and Semicausal 3-D Field Sequences
9.4.2 Reduced Update Spatiotemporal Kalman Filter
9.5 Conclusions
9.6 Problems
References
10 Digital Video Processing
10.1 Interframe Processing
10.2 Motion Estimation and Motion Compensation
10.2.1 Block Matching Method
10.2.2 Hierarchical Block Matching
10.2.3 Overlapped Block Motion Compensation
10.2.4 Pel-Recursive Motion Estimation
10.2.5 Optical flow methods
10.3 Motion-Compensated Filtering
10.3.1 MC-Wiener Filter
10.3.2 MC-Kalman Filter
10.3.3 Frame-Rate Conversion
10.3.4 Deinterlacing
10.4 Bayesian Method for Estimating Motion
10.4.1 Joint Motion Estimation and Segmentation
10.5 Conclusions
10.6 Problems
References
10.7 Appendix: Digital Video Formats
SIF
CIF
ITU 601 Digital TV (aka SMPTE D1 and D5)
ATSC Formats
11 Digital Video Compression
11.1 Intraframe Coding
11.1.1 M-JPEG Pseudo Algorithm
11.1.2 DV Codec
11.1.3 Intraframe SWT Coding
11.1.4 M-JPEG 2000
11.2 Interframe Coding
11.2.1 Generalizing 1-D DPCM to Interframe Coding
11.2.2 MC Spatiotemporal Prediction
11.3 Interframe Coding Standards
11.3.1 MPEG1
11.3.2 MPEG 2—"a Generic Standard"
11.3.3 The Missing MPEG 3—High-Definition Television
11.3.4 MPEG 4—Natural and Synthetic Combined
11.3.5 Video Processing of MPEG-Coded Bitstreams
11.3.6 H.263 Coder for Visual Conferencing
11.3.7 H.264/AVC
11.3.8 Video Coder Mode Control
11.3.9 Network Adaptation
11.4 Interframe SWT Coders
11.4.1 Motion-Compensated SWT Hybrid Coding
11.4.2 3-D or Spatiotemporal Transform Coding
11.5 Scalable Video Coders
11.5.1 MoreonMCTF
11.5.2 Detection of Covered Pixels
11.5.3 Bidirectional MCTF
11.6 Object-Based Video Coding
11.7 Comments on the Sensitivity of Compressed Video
11.8 Conclusions
11.9 Problems
References
12 Video Transmission over Networks
12.1 Video on IP Networks
12.1.1 Overview of IP Networks
12.1.2 Error-Resilient Coding
12.1.3 Transport-Level Error Control
12.1.4 Wireless Networks
12.1.5 Joint Source-Channel Coding
12.1.6 Error Concealment
12.2 Robust SWT Video Coding (Bajic)
12.2.1 Dispersive Packetization
12.2.2 Multiple Description FEC
12.3 Error-Resilience Features of H.264/AVC
12.3.1 Syntax
12.3.2 Data Partitioning
12.3.3 Slice Interleaving and Flexible Macroblock Ordering
12.3.4 Switching Frames
12.3.5 Reference Frame Selection
12.3.6 Intrablock Refreshing
12.3.7 Error Concealment in H.264/AVC
12.4 Joint Source-Network Coding
12.4.1 Digital Item Adaptation (DIA) in MPEG 21
12.4.2 Fine-Grain Adaptive FEC
12.5 Conclusions
12.6 Problems
References
Index
Separate plates (color in original)
Back cover