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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 30000004786574 | TA1637 E44 1999 | Open Access Book | Book | Searching... |
Searching... | 30000004564369 | TA1637 E44 1999 | Open Access Book | Book | Searching... |
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Summary
Summary
This text provides an overview of electronic imaging systems, technology, and practical applications. Written by industry experts, its chapters explore a variety of systems and applications ranging from video compression and handwritten word recognition to colour science and hardware architecture.
Reviews 1
Choice Review
Because this book was published by SPIE Optical Engineering Press, part of the International Society for Optical Engineering, it is primarily for readers interested in applied, industrial electronic imaging technology. Beginning with a brief history of the subject in an introductory chapter that presents applications of image processing, the book moves on to cover, in ten distinct chapters, such topics as video compression standards, multimedia systems, color image processing, enhancement of digital documents, handwritten word and document recognition, and optical and mechanical systems for scanning and digital half toning. Each chapter includes illustrations and ends with an informative list of bibliographical references, all of which are most helpful given the technical nature of the book. Many of the contributing authors are editors for the SPIE/IS&T (Society for Imaging Science and Technology) Journal of Electronic Imaging, culminating in a highly technical book written in a straightforward manner, to help the advanced student/professional in the electronic imaging industry obtain a broader overview of the field. Upper-division undergraduates through professionals; two-year technical program students. J. Natal; Columbia College (IL)
Table of Contents
Chapter 1 IntroductionRobert Weeks |
1.1 Historical Background |
1.2 Applications of Image Processing |
1.3 Image Formation |
1.4 Sampling and Quantization |
1.5 Image Neighbors and Distances |
References |
Chapter 2 Video Compression StandardsFerran Marques and Philippe Salembier |
2.1 Introduction |
2.2 Algorithms for Video Compression |
2.2.1 Predictive techniques for video compression |
2.2.2 Transform techniques for video compression |
2.2.3 Hybrid predictive-transform techniques for video compression |
2.2.3.1 General scheme of a hybrid encoder-decoder |
2.2.3.2 Image prediction for video compression using motion information |
2.2.3.3 Block matching approach for motion estimation and compensation |
2.2.3.4 Fast algorithms |
2.2.3.5 Motion information coding |
2.2.3.6 Prediction error coding |
2.2.3.7 Frame interpolation using motion information |
2.2.3.8 Frame coding using bi-directional prediction |
2.3 Current Video Compression Standards |
2.3.1 H.261: A standard for videophone applications |
2.3.2 MPEG-1: A generic standard for coding of moving pictures for media up to about 1.5 Mbits/s |
2.3.3 MPEG-2: Generic coding of moving pictures |
2.3.4 H.263: Video codec for narrow channels ([ 64 kbits/s) |
2.4 MPEG-4: A Standard Under Development |
2.4.1 MPEG-4: A new set of functionalities |
2.4.2 MPEG-4 natural video |
2.4.3 Video object plane information coding |
2.4.4 Combined mode and separate mode |
2.5 Discussion |
References |
Chapter 3 Multimedia SystemsIrek Defee |
3.1 Multimedia Systems in General |
3.2 Multimedia Applications |
3.3 Multimedia Technology Taxonomy |
3.4 Multimedia System Requirements |
3.5 Personal Computers and Multimedia |
3.5.1 Multimedia extensions to microprocessors |
3.5.2 Architecture of the PC mainboard |
3.6 Multimedia Terminals |
3.7 Operating Systems for Multimedia |
3.8 Storage Devices |
3.9 Media Servers |
3.10 Multimedia Networking |
3.11 Software and Standards |
3.12 System Integration |
3.13 Future Developments |
References |
Chapter 4 Vision and VisualizationRobert Moorhead and Penny Rheingans |
4.1 Vision |
4.1.1 Physiology of the human visual system |
4.1.1.1 The eye |
4.1.1.2 The brain |
4.1.2 Characteristics of human visual perception |
4.1.3 Cognitive influences on perception |
4.2 Visualization |
4.2.1 Types of visualization |
4.2.2 Types of data |
4.2.3 Mappings |
4.2.3.1 Color mapping or pseudo coloring |
4.2.3.2 Contouring |
4.2.3.3 Isosurfaces |
4.2.3.4 Volume rendering |
4.2.3.5 Vector visualization |
4.2.4 Viewing |
4.2.4.1 Softcopy viewing |
4.2.4.2 Hardcopy viewing |
4.3 Perceptual Principles for Visualization Design |
4.3.1 Avoiding unwanted interactions |
4.3.2 Designing effective colormaps |
4.4 Summary |
References |
Chapter 5 Color Image ProcessingRobert Weeks |
5.1 Color Fundamentals |
5.2 Color Models |
5.3 Examples of Color Image Processing |
5.4 Pseudocoloring and Color Displays |
References |
Chapter 6 Enhancement of Digital DocumentsRobert P. Loce and Edward R. Dougherty |
6.1 The Field of Spatial Resolution Conversion and Enhancement |
6.1.1 Other image quality issues |
6.2 Document Enhancement |
6.2.1 Inferential and noninferential image enhancement |
6.2.2 Enhancement by quantization range conversion and redefinition. The contour restoration problem |
6.2.3 Methods of writing enhanced pixels |
6.3 Binary Image Filters |
6.4 Basic Document Processing Operations |
6.4.1 Thickening character strokes that are too thin |
6.4.2 Thinning character strokes that are too thick |
6.4.3 Characters with holes or breaks |
6.4.4 Black point noise removal |
6.5 Spatial Resolution Conversion and Enhancement |
6.5.1 Categories of resolution conversion |
6.5.2 Resolution conversion by multiple parallel filters |
6.5.2.1 Integer conversion |
6.5.2.2 Noninteger conversion |
6.5.3 Resolution conversion by filtering in the resampled space |
References |
Chapter 7 Digital Halftoning for Printing and Display of Electronic ImagesRobert P. Loce and Paul G. Roetling and Ying-wei Lin |
7.1 Introduction |
7.2 Historical Perspective and Overview |
7.2.1 Analog screening |
7.2.2 Template dots |
7.2.3 Noise encoding |
7.2.4 Ordered dither |
7.2.5 Error diffusion |
7.3 Visual Perception |
7.4 Methods of Halftoning |
7.4.1 Noise encoding |
7.4.2 Ordered dither |
7.4.2.1 Implementation |
7.4.2.2 Dispersed-dot ordered dither |
7.4.2.3 Clustered-dot ordered dither |
7.4.2.3.1 Dot growth pattern and tone reproduction, and stability |
7.4.2.3.2 Schematic of analog screen generator for line screen halftoning |
7.4.2.4 Screen frequency vs. number of gray levels |
7.4.2.5 Halftoning, sampling, and aliasing |
7.4.3 Erro diffusion |
7.4.3.1 Fundamental algorithm |
7.4.3.2 Modifications of error diffusion |
7.4.3.3 Mathematical description of error diffusion and edge sharpening effects |
References |
Chapter 8 Document RecognitionJohn C. Handley |
8.1 Document Image Analysis and Understanding |
8.2 Runlength Smoothing Algorithm and Variants |
8.3 Background Covering |
8.4 Document Decoding |
8.5 X-Y Trees |
8.6 Table Recognition: Identification and Analysis |
8.7 Form Recognition |
8.8 Font Identification |
8.8.1 Font extraction by morphological methods |
8.8.2 Projection profiles |
8.9 Conclusion |
8.10 Appendix |
References |
Chapter 9 Lexicon-Driven Handwritten Word RecognitionPaul D. Gader |
9.1 Background |
9.1.1 What is lexicon-driven handwritten word recognition? |
9.1.2 Why is handwritten word recognition difficult? |
9.1.3 Overview of typical system |
9.2 Segmentation Approaches |
9.3 Character Level Processing |
9.3.1 Features |
9.3.2 Character confidence assignment |
9.4 Word Level Processing |
9.4.1 Dynamic programming matching to lexicons |
9.4.2 Estimation of word-level confidence from character level confidence |
9.4.2.1 Baseline dynamic programming algorithm revisited |
9.4.2.2 Robust matching algorithm |
9.5 Experimental Results |
9.6 Conclusion |
9.7 Acknowledgments |
References |
Chapter 10 ScanningYing-wei and Joseph P. Taillie and Leon C. Williams |
10.1 Introduction |
10.2 Fundamentals of the Scanning and Digitization Process |
10.2.1 Overview |
10.2.2 Scanning and sampling |
10.2.3 Quantization |
10.3 Optical and Mechanical Systems |
10.3.1 Paper original support |
10.3.2 Illumination system |
10.3.2.1 Halogen lamp |
10.3.2.2 Fluorescent lamp |
10.3.2.3 LED array |
10.3.2.4 Power supply |
10.3.3 Optical system |
10.3.3.1 Reduction system |
10.3.3.2 Full-page width systems |
10.3.3.3 Wide body systems |
10.3.4 Mechanical system |
10.4 Image Sensor |
10.4.1 CCD sensors |
10.4.2 Contact sensors |
10.4.3 Color CCD sensors |
10.4.4 Color separation |
10.5 Electronics |
10.5.1 A/D conversion |
10.5.2 Non-uniformity correction |
10.6 Factors Affecting Scanned Image Quality |
10.6.1 Scanner MTF |
10.6.2 Scanned image noise |
10.6.3 Motion quality |
10.6.4 Color accuracy |
10.6.4.1 Color filters |
10.6.4.2 Scanner color calibration |
10.6.5 Other factors |
10.7 Image Processing |
10.7.1 Scaling |
10.7.2 Background compensation |
10.7.3 Edge enhancement |
10.7.4 Descreening |
10.7.5 Image segmentation |
10.8 Conclusion |
References |
Chapter 11 Hardware Architecture for Image ProcessingDivyendu Sinha and Edward R. Dougherty |
11.1 Parallelism |
11.1.1 Classification based on instruction and data streams |
11.1.2 Classification based on instruction set |
11.1.3 Cache |
11.2 Pipelined Processors |
11.2.1 General principles |
11.2.2 Instruction pipelining |
11.2.3 Case study: convolution |
11.2.4 Case study: morphological gradient |
11.2.5 Superpipelining |
11.3 Multiple Processors |
11.3.1 Program partitioning and scheduling |
11.3.2 Case study: convolution |
11.4 Massively Parallel Architectures |
11.5 Performance Laws |
11.6 AISI'S Ais Processors |
11.6.1 Linear array processing system |
11.6.2 Processing elements |
11.6.3 Processor operation |
11.6.4 Hit-or-miss transform |
11.6.5 OCR application |
11.7 ITI'S MVC 150/40 Processor |
11.7.1 Image management |
11.7.2 Computational acceleration modules |
References |