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Practical Image and Video Processing Using MATLAB

This book provides a practical introduction to the most important topics in image and video processing, using MATLAB

Up-to-date, technically accurate coverage of essential topics in image and video processing This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.
The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own. ...展开详情收缩
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Practical Image and Video Processing Using MATLAB 文字版PDF

Practical Image and Video Processing Using MATLAB 文字版PDF

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digital image processing using matlab (1)冈萨雷斯

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Digital Image Processing: An Algorithmic Introduction using Java. Springer 2008

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MATLAB.Image.Processing.Toolbox

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digital image processing using matlab

从理论上讲,图像是一种二维的连续函数,然而在计算机上对图像进行数字处理的时候,首先必须对其在空间从理论上讲,图像是一种二维的连续函数,然而在计算机上对图像进行数字处理的时候,首先必须对其在空间和亮度上进行数字化,这就是图像的采样和量化的过程。空间坐标(x,y)的数字化称为图像采样,而幅值数字化称为灰度级量化。和亮度上进行数字化,这就是图像的采样和量化的过程。空间坐标(x,y)的数字化称为图像采样,而幅值数字化称为灰度级量化。

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DESIGN FOR EMBEDDED IMAGE PROCESSING ON FPGAS

Preface xi Acknowledgements xvii 1 Image Processing 1 1.1 Basic Definitions 2 1.2 Image Formation 3 1.3 Image Processing Operations 7 1.4 Example Application 9 1.5 Real-Time Image Processing 11 1.6 Embedded Image Processing 12 1.7 Serial Processing 12 1.8 Parallelism 14 1.9 Hardware Image Processing Systems 18 2 Field Programmable Gate Arrays 21 2.1 Programmable Logic 21 2.1.1 FPGAs vs. ASICs 24 2.2 FPGAs and Image Processing 25 2.3 Inside an FPGA 26 2.3.1 Logic 27 2.3.2 Interconnect 28 2.3.3 Input and Output 29 2.3.4 Clocking 30 2.3.5 Configuration 31 2.3.6 Power Consumption 32 2.4 FPGA Families and Features 33 2.4.1 Xilinx 33 2.4.2 Altera 38 2.4.3 Lattice Semiconductor 44 2.4.4 Achronix 46 2.4.5 SiliconBlue 47 2.4.6 Tabula 47 2.4.7 Actel 48 2.4.8 Atmel 49 2.4.9 QuickLogic 50 2.4.10 MathStar 50 2.4.11 Cypress 51 2.5 Choosing an FPGA or Development Board 51 3 Languages 53 3.1 Hardware Description Languages 56 3.2 Software-Based Languages 61 3.2.1 Structural Approaches 63 3.2.2 Augmented Languages 64 3.2.3 Native Compilation Techniques 69 3.3 Visual Languages 72 3.3.1 Behavioural 73 3.3.2 Dataflow 73 3.3.3 Hybrid 74 3.4 Summary 77 4 Design Process 79 4.1 Problem Specification 79 4.2 Algorithm Development 81 4.2.1 Algorithm Development Process 82 4.2.2 Algorithm Structure 83 4.2.3 FPGA Development Issues 86 4.3 Architecture Selection 86 4.3.1 System Level Architecture 87 4.3.2 Computational Architecture 89 4.3.3 Partitioning between Hardware and Software 93 4.4 System Implementation 96 4.4.1 Mapping to FPGA Resources 97 4.4.2 Algorithm Mapping Issues 100 4.4.3 Design Flow 101 4.5 Designing for Tuning and Debugging 102 4.5.1 Algorithm Tuning 102 4.5.2 System Debugging 104 5 Mapping Techniques 107 5.1 Timing Constraints 107 5.1.1 Low Level Pipelining 107 5.1.2 Process Synchronisation 110 5.1.3 Multiple Clock Domains 111 5.2 Memory Bandwidth Constraints 113 5.2.1 Memory Architectures 113 5.2.2 Caching 116 5.2.3 Row Buffering 117 5.2.4 Other Memory Structures 118 vi Contents 5.3 Resource Constraints 122 5.3.1 Resource Multiplexing 122 5.3.2 Resource Controllers 125 5.3.3 Reconfigurability 130 5.4 Computational Techniques 132 5.4.1 Number Systems 132 5.4.2 Lookup Tables 138 5.4.3 CORDIC 142 5.4.4 Approximations 150 5.4.5 Other Techniques 152 5.5 Summary 154 6 Point Operations 155 6.1 Point Operations on a Single Image 155 6.1.1 Contrast and Brightness Adjustment 155 6.1.2 Global Thresholding and Contouring 159 6.1.3 Lookup Table Implementation 162 6.2 Point Operations on Multiple Images 163 6.2.1 Image Averaging 164 6.2.2 Image Subtraction 166 6.2.3 Image Comparison 170 6.2.4 Intensity Scaling 171 6.2.5 Masking 173 6.3 Colour Image Processing 175 6.3.1 False Colouring 175 6.3.2 Colour Space Conversion 176 6.3.3 Colour Thresholding 192 6.3.4 Colour Correction 193 6.3.5 Colour Enhancement 197 6.4 Summary 197 7 Histogram Operations 199 7.1 Greyscale Histogram 199 7.1.1 Data Gathering 201 7.1.2 Histogram Equalisation 206 7.1.3 Automatic Exposure 210 7.1.4 Threshold Selection 211 7.1.5 Histogram Similarity 219 7.2 Multidimensional Histograms 219 7.2.1 Triangular Arrays 220 7.2.2 Multidimensional Statistics 222 7.2.3 Colour Segmentation 226 7.2.4 Colour Indexing 229 7.2.5 Texture Analysis 231 Contents vii 8 Local Filters 233 8.1 Caching 233 8.2 Linear Filters 239 8.2.1 Noise Smoothing 239 8.2.2 Edge Detection 241 8.2.3 Edge Enhancement 243 8.2.4 Linear Filter Techniques 243 8.3 Nonlinear Filters 248 8.3.1 Edge Orientation 250 8.3.2 Non-maximal Suppression 251 8.3.3 Zero-Crossing Detection 252 8.4 Rank Filters 252 8.4.1 Rank Filter Sorting Networks 255 8.4.2 Adaptive Histogram Equalisation 260 8.5 Colour Filters 261 8.6 Morphological Filters 264 8.6.1 Binary Morphology 264 8.6.2 Greyscale Morphology 269 8.6.3 Colour Morphology 270 8.7 Adaptive Thresholding 271 8.7.1 Error Diffusion 271 8.8 Summary 273 9 Geometric Transformations 275 9.1 Forward Mapping 276 9.1.1 Separable Mapping 277 9.2 Reverse Mapping 282 9.3 Interpolation 285 9.3.1 Bilinear Interpolation 286 9.3.2 Bicubic Interpolation 288 9.3.3 Splines 290 9.3.4 Interpolating Compressed Data 292 9.4 Mapping Optimisations 292 9.5 Image Registration 294 9.5.1 Feature-Based Methods 295 9.5.2 Area-Based Methods 299 9.5.3 Applications 305 10 Linear Transforms 309 10.1 Fourier Transform 310 10.1.1 Fast Fourier Transform 311 10.1.2 Filtering 318 10.1.3 Inverse Filtering 320 10.1.4 Interpolation 321 10.1.5 Registration 322 viii Contents 10.1.6 Feature Extraction 323 10.1.7 Goertzel’s Algorithm 324 10.2 Discrete Cosine Transform 325 10.3 Wavelet Transform 328 10.3.1 Filter Implementations 330 10.3.2 Applications of the Wavelet Transform 335 10.4 Image and Video Coding 336 11 Blob Detection and Labelling 343 11.1 Bounding Box 343 11.2 Run-Length Coding 346 11.3 Chain Coding 347 11.3.1 Sequential Implementation 347 11.3.2 Single Pass Algorithms 348 11.3.3 Feature Extraction 350 11.4 Connected Component Labelling 352 11.4.1 Random Access Algorithms 353 11.4.2 Multiple-Pass Algorithms 353 11.4.3 Two-Pass Algorithms 354 11.4.4 Single-Pass Algorithms 356 11.4.5 Multiple Input Labels 358 11.4.6 Further Optimisations 358 11.5 Distance Transform 359 11.5.1 Morphological Approaches 360 11.5.2 Chamfer Distance 360 11.5.3 Separable Transform 362 11.5.4 Applications 365 11.5.5 Geodesic Distance Transform 365 11.6 Watershed Transform 366 11.6.1 Flow Algorithms 366 11.6.2 Immersion Algorithms 367 11.6.3 Applications 369 11.7 Hough Transform 370 11.7.1 Line Hough Transform 371 11.7.2 Circle Hough Transform 373 11.7.3 Generalised Hough Transform 374 11.8 Summary 375 12 Interfacing 377 12.1 Camera Input 378 12.1.1 Camera Interface Standards 378 12.1.2 Deinterlacing 383 12.1.3 Global and Rolling Shutter Correction 384 12.1.4 Bayer Pattern Processing 384 Contents ix 12.2 Display Output 387 12.2.1 Display Driver 387 12.2.2 Display Content 390 12.3 Serial Communication 393 12.3.1 PS2 Interface 393 12.3.2 I2C 395 12.3.3 SPI 397 12.3.4 RS-232 397 12.3.5 USB 398 12.3.6 Ethernet 398 12.3.7 PCI Express 399 12.4 Memory 400 12.4.1 Static RAM 400 12.4.2 Dynamic RAM 401 12.4.3 Flash Memory 402 12.5 Summary 402 13 Testing, Tuning and Debugging 405 13.1 Design 405 13.1.1 Random Noise Sources 406 13.2 Implementation 409 13.2.1 Common Implementation Bugs 410 13.3 Tuning 412 13.4 Timing Closure 412 14 Example Applications 415 14.1 Coloured Region Tracking 415 14.2 Lens Distortion Correction 418 14.2.1 Characterising the Distortion 419 14.2.2 Correcting the Distortion 421 14.3 Foveal Sensor 424 14.3.1 Foveal Mapping 425 14.3.2 Using the Sensor 429 14.4 Range Imaging 429 14.4.1 Extending the Unambiguous Range 431 14.5 Real-Time Produce Grading 433 14.5.1 Software Algorithm 434 14.5.2 Hardware Implementation 436 14.6 Summary 439 References 441 Index 475 x Content

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Fundamentals of Digital Signal Processing using MATLAB

Fundamentals of Digital Signal Processing Using MATLAB (2nd Edition) by Robert J. Schilling CL-Engineering | ISBN : 084006909X | January 1, 2011 | 788 pages | This second edition text focuses on the fundamentals of digital signal processing with an emphasis on practical applications. In order to motivate students, many of the examples illustrate the processing of speech and music. This theme is also a focus of the course software that features facilities for recording and playing sound on a standard PC. The accompanying website contains a comprehensive MATLAB software package called the Fundamentals of Digital Signal Processing (FDSP) toolbox version 2.0.

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Video and Image Processing Suite

This document describes the Altera Video and Image Processing Suite collection of IP cores that ease the development of video and image processing designs.

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