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E-raamat: Digital Image Processing with Application to Digital Cinema [Taylor & Francis e-raamat]

(Consulatant, Micro USA, San Diego, CA and professor at San Diego State University for twenty years)
  • Formaat: 400 pages
  • Ilmumisaeg: 19-Dec-2005
  • Kirjastus: Focal Press
  • ISBN-13: 9780080477275
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 161,57 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 230,81 €
  • Säästad 30%
Digital Image Processing with Application to Digital CinemaSuurem pilt
  • Formaat: 400 pages
  • Ilmumisaeg: 19-Dec-2005
  • Kirjastus: Focal Press
  • ISBN-13: 9780080477275
Teised raamatud teemal:
Taylor & Francis e-raamatudRohkem infot Taylor & Francis e-raamatute kohta
Raamatu kodulehekülg: https://www.taylorfrancis.com/books/9780080477275
With crystal clarity, this book conveys the most current principles in digital image processing, providing both the background theory and the practical applications to various industries, such as digital cinema, video compression, and streaming media.

This book contains tons of useful features, including:
* a chapter on the role of human vision in image visualization,
* the MATLAB codes used to generate most of the figures and tables listed in the book, as well as a few MATLAB projects,
* a 24-pg color insert
* case studies to illustrate the practical application of the theory.
Foreword xv
Preface xvii
Acknowledgments xxi
Introduction
1(12)
Background
1(1)
Enhancement
1(3)
Compression
4(2)
Restoration
6(2)
Computed Tomography
8(1)
Image Analysis
8(3)
Summary
11(2)
References
11(2)
Two-Dimensional Signals, Systems, and Discrete Fourier Transform
13(34)
Two-Dimensional Discrete Signals
13(2)
Two-Dimensional Discrete Systems
15(2)
Linear Systems
15(1)
Space Invarient Systems
16(1)
System Response via 2-D Convolution
16(1)
Causal and Stable Systems
17(1)
Two-Dimensional Discrete Fourier Transform
17(2)
Frequency Response
19(4)
Two-Dimensional Filtering
23(4)
FIR Filter Design
27(17)
Separable FIR Filters
27(1)
Window-Based Methods
27(12)
Frequency Sampling Technique
39(1)
Optimal Design Techniques
40(1)
Nonseparable FIR Filters
41(3)
Summary
44(3)
References
44(3)
Human Visual Perception
47(26)
Introduction
47(1)
Brightness Perception
47(12)
Intensity, Luminance, and Brightness
47(3)
Simultaneous Contrast
50(2)
Mach Bands
52(2)
Transfer Function of the HVS
54(1)
Monochrome Vision Model
55(2)
Visual Masking and an Improved HVS Model
57(2)
Color Perception
59(11)
Color-Matching Functions
61(2)
Color Coordinate Systems
63(1)
CIE XYZ Primaries
64(2)
NTSC Receiver and Transmission Primaries
66(3)
HVS Model for Color Vision
69(1)
Opponent Color Model
70(1)
Summary
70(3)
References
71(2)
Image Acquisition
73(24)
Introduction
73(1)
Image Sensors
73(9)
CCD Sensors
74(2)
Full-Frame Architecture
76(1)
Interline Architecture
76(1)
Frame-Transfer CCD
77(2)
CMOS Sensors
79(1)
Color Sensors
79(3)
Image Sampling
82(5)
Image Quantization
87(3)
Uniform Quantization
87(1)
Optimal Quantization
88(2)
Image Scanning
90(3)
Interlaced and Progressive Scanning
90(1)
Color Image Scanning
91(1)
Color Encoding in Digital Video
91(2)
Film-to-Digital Conversion
93(1)
Summary
94(3)
References
95(2)
Image Inhancement
97(26)
Background
97(1)
Point Processing
97(7)
Logarithmic Transformation
98(1)
Contrast Stretching
98(3)
Histogram Modification
101(1)
Histogram Equalization
101(3)
Adaptive Histogram Modification
104(1)
Neighborhood Processing
104(13)
Simple Mask Operations
106(3)
Two-Dimensional Filters Satisfying Specified Frequency Responses
109(2)
Median Filtering
111(6)
Color Image Enhancement
117(3)
Summary
120(3)
References
121(2)
Discrete Transforms for Image Processing
123(24)
Introduction
123(1)
Unitary Transforms
123(17)
One-Dimensional Unitary Transforms
123(1)
One-Dimensional DFT
124(1)
One-Dimensional Discrete Cosine Transform (DCT)
125(1)
One-Dimensional Discrete Sine Transform (DST)
126(1)
One-Dimensional Discrete Hartley Transform
127(1)
Hadamard, Haar, and Slant Transforms
128(5)
Two-Dimensional Discrete Transforms
133(4)
Some Properties of Unitary Transform
137(3)
Karhunen-Loeve Transform
140(4)
Choice of a Transform
144(1)
Summary
144(3)
References
144(3)
Wavelet Transform
147(46)
Introduction
147(2)
Continuous Wavelet Transform
149(2)
The Wavelet Series
151(9)
Discrete Wavelet Transform
160(1)
Implementation of the Discrete Wavelet Transform
160(4)
Relationship of Scaling and Wavelet Filters to Wavelets
164(7)
Orthogonal Discrete Wavelet Transform
166(2)
Biorthogonal Discrete Wavelet Transform
168(3)
Construction of Wavelets
171(1)
Two-Dimensional Discrete Wavelet Transform
171(18)
Summary
189(4)
References
189(4)
Image Compression
193(92)
Introduction
193(6)
Image Fidelity Criterion
197(1)
Quantitative Measures
197(1)
Subjective Measures
198(1)
Lossless Compression
199(13)
Elements of Information Theory
199(3)
Huffman Coding
202(3)
Run-Length Coding
205(1)
Arithmetic Coding
206(2)
Golomb--Rice (GR) Coding
208(4)
Predictive Coding
212(6)
One-Dimensional DPCM
212(3)
Adaptive DPCM
215(3)
Two-Dimensional DPCM
218(1)
Transform Coding
218(13)
Choice of a Transform
220(1)
Optimal Bit Allocation
220(2)
Quantizer Design
222(4)
Entropy Coder
226(4)
Variable Block Size DCT Coder
230(1)
Compression in the Wavelet Domain
231(24)
Choice of Wavelets
232(2)
Quantization
234(1)
Zero-Tree Wavelet Coding
234(10)
JPEG2000 Standard
244(11)
Video Coding Principles
255(23)
Temporal Prediction in the Pixel Domain
256(1)
Motion Estimation
256(3)
Wavelet-Based Interframe Coding
259(1)
Interframe Coding Using Three-Dimensional DCT
260(1)
Temporal Depth
261(1)
Three-Dimensional DCT
261(1)
Quantization
262(1)
Zigzag Scanning
263(1)
Entropy Coding
263(1)
Role of Human Visual Perception in Image and Video Coding
263(1)
Quantization Matrix for DCT Domain Coding
263(2)
Quantization Matrix for Wavelet Domain Coding
265(1)
Use of Spatial and Temporal Masking Models
266(4)
MPEG Standard
270(8)
Summary
278(7)
References
280(5)
Application of Image Compression to Digital Cinema
285(86)
Introduction
285(1)
Digital Cinema Technology Requirements
285(4)
Image Resolution and Format
285(1)
Digital Projector
286(1)
Image Compression System
287(2)
Case Study
289(8)
Qualcomm's Digital Cinema System
289(1)
Adaptive Block-Size DCT Encoder
290(2)
ABSDCT Decoder
292(1)
Qualcomm's Decoder ASIC
292(3)
Digital Cinema Using Motion JPEG2000 Standard
295(1)
MJ2K Image Resolution and Format
295(1)
Compression in the Wavelet Domain
295(1)
MJ2K File Format
295(1)
Error Resilience
296(1)
Concluding Remarks
297(4)
References
298(3)
Appendices
Continuous and Discrete Fourier Transforms
301(4)
Continuous Fourier Transform
301(1)
Properties of Continuous Fourier Transform
302(1)
Discrete Fourier Transform
303(2)
Radiometric and Photometric Quantities
305(4)
Radiometric Quantities
305(1)
Radiant Energy
305(1)
Radiant Flux
305(1)
Radiant Exitance
305(1)
Irradiance
305(1)
Radiant Intensity
306(1)
Radiance
306(1)
Photometric Quantities
306(1)
Luminous Flux
306(1)
Lumens
307(1)
Luminous Intensity
307(1)
Luminance
307(1)
Illumanation
308(1)
MATLAB M Files for Selected
Chapters
309(58)
M Files from
Chapter 2
309(4)
M Files from
Chapter 3
313(4)
M Files from
Chapter 4
317(1)
M Files from
Chapter 5
318(13)
M Files from
Chapter 6
331(9)
M Files from
Chapter 7
340(6)
M Files from
Chapter 8
346(21)
Suggested MATLAB-Oriented Projects
367(4)
Projects in
Chapter 2
367(1)
Effect of Filtering an Image
367(1)
Nonlinear Filtering
367(1)
Phase Distortion
367(1)
Projects in
Chapter 3
368(1)
Contrast Sensitivity
368(1)
Spatial Masking Effect
368(1)
Color Sensitivity
368(1)
Projects in
Chapter 5
368(1)
Adaptive Histogram Equalization
368(1)
Noise Cleaning
369(1)
Color Image Enhancement
369(1)
Projects in
Chapter 8
369(1)
DPCM
369(1)
DPCM Using GR Coding
369(1)
Transform Coder
369(1)
Transform Coder for Color Images
370(1)
Encoder Using Discrete Wavelet Transform
370(1)
DWT Encoder for Color Image Compression
370(1)
Motion Estimation
370(1)
Index 371


K.S. Thyagarajan is a researcher with Micro USA, working on the development of algorithms to process remote surveillance iamges. As a principal engineer for Qualcomm for five years, he researched and developed high quality video compression systems for digital cinema applications. As a professor at San Diego State University for twenty years he taught courses in circuits, signals & systems, analog and digital communications, digital signal processing and image processing and conducted research in video compression.
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