Muutke küpsiste eelistusi

E-raamat: Document and Image Compression

Edited by (University of Siena, Italy)
Teised raamatud teemal:
  • Formaat - PDF+DRM
  • Hind: 58,49 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Raamatukogudele
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

Although it's true that image compression research is a mature field, continued improvements in computing power and image representation tools keep the field spry. Faster processors enable previously intractable compression algorithms and schemes, and certainly the demand for highly portable high-quality images will not abate. Document and Image Compression highlights the current state of the field along with the most probable and promising future research directions for image coding.

Organized into three broad sections, the book examines the currently available techniques, future directions, and techniques for specific classes of images. It begins with an introduction to multiresolution image representation, advanced coding and modeling techniques, and the basics of perceptual image coding. This leads to discussions of the JPEG 2000 and JPEG-LS standards, lossless coding, and fractal image compression. New directions are highlighted that involve image coding and representation paradigms beyond the wavelet-based framework, the use of redundant dictionaries, the distributed source coding paradigm, and novel data-hiding techniques. The book concludes with techniques developed for classes of images where the general-purpose algorithms fail, such as for binary images and shapes, compound documents, remote sensing images, medical images, and VLSI layout image data.

Contributed by international experts, Document and Image Compression gathers the latest and most important developments in image coding into a single, convenient, and authoritative source.
Part I State of the Art
Multiresolution Analysis for Image Compression
3(32)
Luciano Alparone
Fabrizio Argenti
Tiziano Bianchi
Introduction
3(1)
Wavelet Analysis and Filter Banks
4(12)
Continuous Wavelet Transform and Frames
5(1)
Multiresolution Spaces
5(1)
Multiresolution Analysis and Filter Banks
6(2)
Orthogonal and Biorthogonal Filter Banks
8(1)
Reconstruction at Boundaries
9(2)
Lifting Scheme
11(1)
Implementing Wavelet Transforms via Lifting
12(2)
Wavelet Decomposition of Images
14(1)
Quantization of Mallat's DWT
15(1)
Enhanced Laplacian Pyramid
16(4)
Quantization of ELP with Noise Feedback
18(2)
Coding Schemes
20(12)
Embedded Zero-Tree Wavelet Coder
20(2)
Set Partitioning in Hierarchical Trees Coder
22(4)
Embedded Block Coding with Optimized Truncation
26(1)
Content-Driven ELP Coder
27(2)
Synchronization Tree
29(1)
Results
30(2)
Conclusions
32(3)
References
32(3)
Advanced Modeling and Coding Techniques for Image Compression
35(34)
David Taubman
Introduction
35(1)
Introduction to Entropy and Coding
36(4)
Information and Entropy
36(1)
Fixed- and Variable-Length Codes
37(1)
Joint and Conditional Entropy
38(2)
Arithmetic Coding and Context Modeling
40(12)
From Coding to Intervals on (0,1)
40(2)
Elias Coding
42(1)
Practical Arithmetic Coding
43(4)
Conditional Coding and Context Modeling
47(1)
Adaptive Probability Estimation
48(2)
Binary Arithmetic Coding Is Enough
50(1)
Arithmetic Coding Variants
50(1)
Arithmetic Coding in JBIG
51(1)
Information Sequencing and Embedding
52(6)
Quantization
52(1)
Multiresolution Compression with Wavelets
53(1)
Embedded Quantization and Bit-Plane Coding
54(2)
Fractional Bit-Plane Coding
56(1)
Coding vs. Ordering
57(1)
Overview of EBCOT
58(7)
Embedded Block Coding Primitives
58(2)
Significance Coding
60(1)
Sign Coding
60(1)
Magnitude Refinement Coding
61(1)
Fractional Bit-Plane Scan
61(1)
Optimal Truncation
62(1)
Multiple Quality Layers
63(2)
Reflections
65(4)
References
66(3)
Perceptual Aspects of Image Coding
69(18)
Alessandro Neri
Marco Carli
Sanjit K. Mitra
Introduction
69(1)
The Human Vision System
70(2)
Physiological Models
72(4)
Perceptual Distortion Metrics
76(2)
Evaluation of the JND Threshold
78(1)
Effects of Perception in DCT Domain
79(2)
Perception Metrics in the Wavelet Domain
81(3)
Conclusions
84(3)
References
84(3)
The JPEG Family of Coding Standards
87(26)
Enrico Magli
Introduction
88(1)
A Brief History of the JPEG Family of Standards
88(1)
The JPEG Standard
89(7)
Transform
89(1)
Quantization
90(1)
Entropy Coding
91(1)
Huffman Coding
91(2)
Arithmetic Coding
93(1)
Lossless Mode
94(1)
Progressive and Hierarchical Encoding
95(1)
Codestream Syntax
95(1)
The JPEG-LS Standard
96(5)
Context-Based Prediction
97(1)
Entropy Coding
98(1)
Golomb coding
98(1)
Run Mode
99(1)
Near-Lossless Mode
99(1)
JPEG-LS Part 2
99(1)
Codestream Syntax
100(1)
The JPEG 2000 Standard
101(8)
Transform and Quantization
101(1)
DC Level Shifting
101(1)
Multicomponent Transformation
102(1)
Wavelet Transformation
102(1)
Quantization
103(1)
Data Organization
103(1)
Entropy Coding
104(1)
Codestream Syntax
105(1)
Progression Orders
Codestream Generation
Advanced Features
106(1)
Region of Interest Coding
106(1)
Error Resilience
107(1)
Other Parts of the Standard
108(1)
Part 2 --- Extensions
108(1)
Part 3 --- Motion JPEG 2000
108(1)
Other Parts
108(1)
Advanced Research Related to Image-Coding Standards
109(1)
DCT-Based Coding
109(1)
Wavelet-Based Coding and Beyond
109(1)
Available Software
110(3)
JPEG
110(1)
JPEG-LS
110(1)
JPEG 2000
110(1)
References
110(3)
Lossless Image Coding
113(32)
Soren Forchhammer
Nasir Memon
Introduction
113(1)
General Principles
114(7)
Prediction
115(1)
Context Modeling
116(1)
Entropy Coding
117(1)
Huffman Coding
117(2)
Arithmetic Coding
119(2)
Lossless Image Coding Methods
121(8)
JPEG Lossless
121(1)
Huffman Coding Procedures
121(1)
Arithmetic Coding Procedures
122(1)
Context-Based Adaptive Lossless Image Coding
123(1)
Gradient-Adjusted Predictor
124(1)
Coding Context Selection and Quantization
125(1)
Context Modeling of Prediction Errors and Error Feedback
126(1)
Entropy Coding of Prediction Errors
126(1)
JPEG-LS
127(1)
Reversible Wavelets --- JPEG2000
128(1)
Experimental Results
129(1)
Optimizations of Lossless Image Coding
129(5)
Multiple Prediction
130(1)
Optimal Context Quantization
131(3)
Application Domains
134(11)
Color and Multiband
134(1)
Predictive Techniques
134(1)
Band Ordering
135(1)
Interband Prediction
135(1)
Error Modeling and Coding
136(1)
Hyperspectral Images
136(1)
Reversible Transform-Based Techniques
137(1)
Video Sequences
137(2)
Color-Indexed Images and Graphics
139(1)
References
140(5)
Fractal Image Compression
145(34)
Raouf Hamzaoui
Dietmar Saupe
Introduction
145(3)
The Fractal Image Model
148(6)
Variants
153(1)
Image Partitions
154(3)
Quadtrees
155(1)
Other Hierarchical Partitions
155(1)
Split--Merge Partitions
156(1)
Encoder Complexity Reduction
157(5)
Feature Vectors
157(2)
Classification Schemes
159(1)
Jacquin's Approach
159(1)
Classification by Intensity and Variance
159(1)
Clustering Methods
160(1)
Tree-Structured Methods
160(1)
Multiresolution Approaches
160(1)
Fast Search via Fast Convolution
161(1)
Fractal Image Compression without Searching
162(1)
Decoder Complexity Reduction
162(2)
Fast Decoding with Orthogonalization
162(1)
Hierarchical Decoding
162(1)
Codebook Update
163(1)
Other Methods
164(1)
Attractor Coding
164(2)
Rate-Distortion Coding
166(1)
Extensions
167(1)
Hybrid Methods
167(1)
Channel Coding
167(1)
Progressive Coding
167(1)
Postprocessing
167(1)
Compression of Color Images
168(1)
Video Coding
168(1)
Applications
168(1)
State of the Art
168(2)
Conclusion
170(9)
Acknowledgments
171(1)
References
172(7)
Part II New Directions
Beyond Wavelets: New Image Representation Paradigms
179(28)
Hartmut Fuhr
Laurent Demaret
Felix Friedrich
Introduction
179(1)
The Problem and Some Proposed Solutions
180(13)
Wedgelets
184(3)
Curvelets
187(5)
Alternative Approaches
192(1)
Digital Wedgelets
193(3)
Rapid Summation on Wedge Domains: Discrete Green's Theorem
194(1)
Implementation
195(1)
Digital Curvelets: Contourlets
196(3)
Application to Image Compression
199(5)
Experimental Approximation Properties
199(3)
Coding Schemes
202(2)
Tentative Conclusions and Suggestions for Further Reading
204(3)
Acknowledgment
205(1)
References
205(2)
Image Coding Using Redundant Dictionaries
207(28)
Pierre Vandergheynst
Pascal Frossard
Introduction
207(2)
A Quick Glance at Digital Image Compression
208(1)
Limits of Current Image Representation Methods
209(1)
Redundant Expansions
209(21)
Benefits of Redundant Transforms
209(1)
Nonlinear Algorithms
210(1)
A Wealth of Algorithms
210(1)
Highly Nonlinear Approximations
210(2)
Greedy Algorithms: Matching Pursuit
212(2)
A Scalable Image Encoder
214(1)
Overview
214(1)
Matching Pursuit Search
215(1)
Generating Functions of the Dictionary
215(1)
Anisotropy and Orientation
216(1)
Dictionary
217(1)
Coding Stage
218(1)
Coefficient Quantization
218(2)
Rate Control
220(1)
Experimental Results
220(1)
Benefits of Anisotropy
220(2)
Coding Performance
222(1)
Extension to Color Images
223(4)
High Adaptivity
227(1)
Importance of Adaptivity
227(1)
Spatial Adaptivity
227(2)
Rate Scalability
229(1)
Discussions and Conclusions
230(5)
Discussions
230(1)
Extensions and Future Work
231(1)
Acknowledgments
231(1)
References
232(3)
Distributed Compression of Field Snapshots in Sensor Networks
235(20)
Sergio D. Servetto
Introduction
235(5)
Distributed Image Coding and Wireless Sensor Networks
236(1)
The Sensor Broadcast Problem
236(1)
Problem Formulation
236(1)
Relevance of the Problem
237(1)
Data Compression Structures
238(1)
Data Compression Using Independent Encoders
239(1)
Exploiting Correlations in the Source
239(1)
Organization of the
Chapter
239(1)
Distributed Compression of Sensor Measurements
240(3)
Information-Theoretic Bounds for Bandlimited Images
240(1)
Distributed Computation of Decorrelating Transforms
241(1)
Images Constrained by Physical Laws
241(2)
Transforms for Distributed Decorrelation of Bandlimited Images
243(5)
The ``Drop-Data'' Transform
243(1)
Linear Signal Expansions with Bounded Communication
244(1)
Wavelets and Sensor Broadcast
244(1)
Definition of the Coding Strategy
244(2)
Differentiating between Local and Global Communication Requirements
246(1)
Communication within a Coherence Region
246(1)
Global Communication
246(1)
In Summary
247(1)
Physically Constrained Nonbandlimited Images
248(2)
Wave Field Models
248(1)
Sampling and Interpolation
249(1)
Compression
250(1)
Literature Review
250(1)
Conclusion
251(4)
References
251(4)
Data Hiding for Image and Video Coding
255(30)
Patrizio Campisi
Alessandro Piva
Introduction
255(1)
Data Hiding for Image and Video Compression
256(12)
Data in Image
257(7)
Data in Video
264(4)
Data Hiding for Error Concealment
268(9)
Error Concealment for Resynchronization
269(1)
Error Concealment for the Recovery of MV Values in Lost Blocks
270(1)
Error Concealment for the Recovery of Pixel Values in Lost Blocks
271(4)
Recovery of Pixel Values in Lost Blocks through Self-Embedding Methods
275(2)
Final Comments
277(1)
Further Readings
278(7)
Acknowledgments
278(1)
References
278(7)
Part III Domain-Specific Coding
Binary Image Compression
285(14)
Charles Boncelet
Introduction
285(1)
Binary Images
285(1)
Groups 3 and 4 Facsimile Algorithms
286(1)
JBIG and JBIG2
287(5)
JBIG
287(2)
JBIG2
289(3)
Context Weighting Applied to Binary Compression
292(4)
A Quick Introduction to Context Weighting
292(2)
Application to Binary Image Compression
294(1)
New Compression Algorithms
295(1)
Conclusions
296(3)
References
296(3)
Two-Dimensional Shape Coding
299(24)
Joern Ostermann
Anthony Vetro
Introduction
299(4)
Shape Coding Overview
301(1)
Related Work
301(1)
Implicit Shape Coding
301(1)
Bitmap-Based Shape Coding
302(1)
Contour-Based Shape Coding
302(1)
MPEG-4 Shape Coding
303(1)
Chapter Organization
303(1)
MPEG-4 Shape Coding Tools
303(5)
Shape Representation
304(1)
Binary Shape Coding
304(1)
Intra-Mode
305(1)
Inter-Mode
306(1)
Evaluation Criteria for Coding Efficiency
307(1)
Gray-Scale Shape Coding
307(1)
Objects with Constant Transparency
307(1)
Objects with Arbitrary Transparency
307(1)
Texture Coding of Boundary Blocks
307(1)
Video Coder Architecture
308(1)
Codec Optimization
308(8)
Preprocessing
309(1)
Rate--Distortion Models
310(3)
Rate Control
313(1)
Buffering Policy
313(1)
Bit Allocation
314(1)
Error Control
314(1)
Post-Processing
315(1)
Composition and Alpha Blending
315(1)
Error Concealment
315(1)
Applications
316(2)
Surveillance
316(2)
Interactive TV
318(1)
Concluding Remarks
318(5)
References
319(4)
Compressing Compound Documents
323(28)
Ricardo L. de Queiroz
Introduction
323(1)
Raster Imaging Models
324(3)
Mixed Raster Content
324(1)
Region Classification
325(1)
Other Imaging Models
326(1)
DjVu
326(1)
Soft Masks for Blending
327(1)
Residual Additive Planes
327(1)
MRC for Compression
327(9)
Object Segmentation versus Region Classification
329(1)
Redundant Data and Segmentation Analysis
330(3)
Plane Filling
333(3)
A Simple MRC: JPEG+MMR+JPEG
336(8)
Computing Rate and Distortion per Block
337(1)
Optimized Thresholding as Segmentation
338(2)
Fast Thresholding
340(1)
Performance
341(3)
MRC within JPEG 2000
344(7)
JP2-Based JPM
347(1)
Conclusions
348(1)
References
349(2)
Trends in Model-Based Coding of Multidimensional Medical Data
351(38)
Gloria Menegaz
Introduction
352(1)
Requirements
353(1)
State of the Art
354(10)
2-D Systems
354(1)
Lossless Techniques
355(1)
Lossy Techniques
356(1)
DCT-Based Techniques
356(1)
Wavelet-Based Techniques
357(3)
3-D Systems
360(1)
3-D Set Partitioning Hierarchical Trees
360(1)
Cube Splitting
361(1)
3-D Quadtree Limited
361(1)
CS-Embedded Block Coding (CS-EBCOT)
361(1)
3-D DCT
362(1)
3-D ROI-Based Coding
362(1)
Model-Based Coding
363(1)
3-D/2-D ROI-Based MLZC: A 3-D Encoding/2-D Decoding Object-Based Architecture
364(1)
Object-Based Processing
365(3)
3-D Analysis vs. 2-D Reconstruction
368(1)
Multidimensional Layered Zero Coding
368(7)
Layered Zero Coding
368(1)
MLZC Coding Principle
369(1)
Spatial Conditioning
369(2)
Interband Conditioning
371(1)
Bitstream Syntax
371(1)
Global Progressive (G-PROG)
371(1)
Layer per Layer Progressive (LPL-PROG)
371(1)
Layer per Layer (LPL) Mode
372(1)
3-D Object-Based Coding
372(1)
Embedded Zerotree Wavelet-Based Coding
373(1)
Multidimensional Layered Zero Coding
374(1)
3-D/2-D MLZC
374(1)
3-D/2-D Object-Based MLZC
374(1)
Results and Discussion
375(10)
Datasets
375(2)
3-D/2-D MLZC
377(2)
3-D Object-Based MLZC
379(1)
System Characterization
379(2)
Object-Based Performance
381(3)
3-D/2-D Object-Based MLZC
384(1)
Conclusions
385(4)
References
386(3)
Remote-Sensing Image Coding
389(24)
Bruno Aiazzi
Stefano Baronti
Cinzia Lastri
Introduction
389(1)
Quality Issues in Remote-Sensing Data Compression
389(2)
Distortion Measures
391(2)
Radiometric Distortion
391(1)
Spectral Distortion
392(1)
Advanced Compression Algorithms for Remote-Sensing Images
393(2)
Context Modeling
394(1)
Near-Lossless Compression through 3D Causal DPCM
395(1)
Near-Lossless Image Compression through Noncausal DPCM
396(3)
Experimental Results
399(10)
Multispectral Data
399(2)
Hyperspectral Data
401(5)
SAR Focused Data
406(1)
SAR Raw Data
407(2)
Conclusions
409(4)
References
409(4)
Lossless Compression of VLSI Layout Image Data
413(14)
Vito Dai
Avideh Zakhor
Introduction
413(1)
Overview of C4
414(1)
Context-Based Prediction Model
415(2)
Copy Regions and Segmentation
417(3)
Hierarchical Combinatorial Coding
420(2)
Extension to Gray Pixels
422(1)
Compression Results
423(2)
Summary
425(2)
Acknowledgment
425(1)
References
426(1)
Index 427