پردازش و کدگذاری سیگنال، تصویر و ویدئو چندبعدی، ویرایش دوم

This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: New appendices on random processes, information theory New coverage of image analysis – edge detection, linking, clustering, and segmentation Expanded coverage on image sensing and perception, including color spaces. Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC. Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding. More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming. New coverage of super-resolution methods for image and video. Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected. New chapters on introductory random processes, information theory, and image enhancement and analysis Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC) Multidimensional Signal, Image, and Video Processing and Coding ......Page 2 Copyright ......Page 3 Preface......Page 4 Acknowledgments......Page 6 Two-Dimensional Signals......Page 8 Separable Signals......Page 11 Periodic Signals......Page 13 General Periodicity......Page 14 2-D Discrete-Space Systems......Page 16 2-D Convolution......Page 17 Properties of 2-D Convolution or Convolution Algebra......Page 18 Stability in 2-D Systems......Page 19 2-D Discrete-Space Fourier Transform......Page 20 Inverse 2-D Fourier Transform......Page 23 Fourier Transform of 2-D or Spatial Convolution......Page 26 Some Important Properties of the FT Operator......Page 27 Some Useful Fourier Transform Pairs......Page 28 Symmetry Properties of the Fourier Transform......Page 32 Symmetry Properties of Real-valued Signals......Page 33 2-D Fourier Continuous Transform......Page 34 Projection-Slice Theorem......Page 36 Problems......Page 37 References......Page 41 Sampling Theorem—Rectangular Case......Page 43 Reconstruction Formula......Page 47 Ideal Rectangular Sampling......Page 50 Sampling Theorem—General Regular Case......Page 56 Hexagonal Reconstruction Formula......Page 60 Downsampling by Integers M1 x M2......Page 64 Ideal Decimation......Page 67 Upsampling by Integers L1 x L2......Page 70 Ideal Interpolation......Page 71 Sample-Rate Change—General Case......Page 72 General Downsampling......Page 73 Problems......Page 75 References......Page 80 Linear Spatial or 2-D Systems......Page 81 Z-Transforms......Page 85 Regions of Convergence......Page 87 More General Case......Page 90 Some Z-Transform Properties......Page 91 Linear Mapping of Variables......Page 93 Inverse Z-Transform......Page 94 2-D Filter Stability......Page 98 Second Quadrant Support......Page 100 Root Maps......Page 104 Stability Criteria for NSHP Support Filters......Page 106 Conclusions......Page 108 Problems......Page 109 References......Page 112 Discrete Fourier Series......Page 114 Properties of the DFS Transform......Page 116 Periodic Convolution......Page 118 Shifting or Delay Property......Page 119 Discrete Fourier Transform......Page 120 DFT Properties......Page 123 Proof of DFT Circular Shift Property 5......Page 125 Relation of DFT to Fourier Transform......Page 127 Effect of Sampling in Frequency......Page 128 Interpolating the DFT......Page 129 2-D Discrete Cosine Transform......Page 130 Review of 1-D DCT......Page 131 Some 1-D DCT Properties......Page 134 Symmetric Extension in 2-D DCT......Page 136 Comments......Page 137 Ideal Filter Case......Page 138 1-D SWT with Finite Order Filters......Page 142 2-D SWT with Finite Impulse Response (FIR) Filters......Page 145 Relation of SWT to Wavelets......Page 146 Fast DFT Algorithm......Page 148 Fast DCT Methods......Page 149 Sectioned Convolution Methods......Page 150 Problems......Page 151 References......Page 155 FIR Window Function Design......Page 157 Common 1-D Continuous Time Windows......Page 158 Design by Transformation of 1-D Filter......Page 164 Projection Onto Convex Sets......Page 170 Basic POCS Algorithm......Page 171 2-D Recursive Filter Design......Page 172 Typical Design Criteria......Page 173 Padé Approximation......Page 174 Prony's Method (Shank's)......Page 176 Fully Recursive Filter Design......Page 178 Observations......Page 179 Subband/Wavelet Filter Design......Page 181 Wavelet (Biorthogonal) Filter Design Method......Page 184 Conclusions......Page 188 Problems......Page 189 References......Page 194 Light and Luminance......Page 196 Still Image Visual Properties......Page 198 Weber's Law......Page 199 Contrast Sensitivity Function......Page 200 Local Contrast Adaptation......Page 202 Time-Variant Human Visual System Properties......Page 203 Color......Page 206 Chromaticity Values......Page 208 Color Processing......Page 210 Color Spaces......Page 212 International Telecommunication Union (ITU) Recomendation 709......Page 213 sRGB......Page 214 Electronic Sensors......Page 215 Sensor Fill Factor......Page 217 Film......Page 218 Image and Video Display......Page 219 Gamma......Page 220 High Dynamic Range and Tone Mapping......Page 221 Problems......Page 222 References......Page 223 Box Filter......Page 225 Gaussian Filter......Page 226 Prewitt Operator......Page 227 Sobel Operator......Page 228 Laplacian Filter......Page 229 Linear Filtering......Page 230 Filtering in Intensity Domain......Page 232 Median Filtering......Page 233 Edge Detection......Page 237 Edge Linking......Page 240 Segmentation......Page 241 Simple Thresholding......Page 242 Optimal Values for the rk......Page 244 Region Growing......Page 247 Object Segmentation......Page 250 Template Matching......Page 252 Problems......Page 255 References......Page 257 Two-Dimensional Random Fields ......Page 259 Filtering a 2-D Random Field......Page 262 Autoregressive Random Signal Models......Page 265 Estimation for Random Fields......Page 267 Infinite Observation Domain......Page 268 Wiener Filter—Alternative Derivation......Page 269 NSHP Causal Wiener Filter......Page 271 1-D Kalman Filter......Page 272 1-D Kalman Filter Equations......Page 274 Scalar Kalman Filtering Equations......Page 275 2-D Kalman Filtering......Page 276 Approximate RUKF......Page 278 LSI Estimation and Restoration Examples with RUKF......Page 279 Inhomogeneous Gaussian Estimation......Page 284 Inhomogeneous Estimation with RUKF......Page 286 Estimation in the Subband/Wavelet Domain......Page 287 Gauss-Markov Image Model......Page 291 Compound Gauss-Markov Image Model......Page 294 Simulated Annealing......Page 295 Extensions of Simulated Annealing......Page 299 Expectation-Maximization Algorithm Approach......Page 300 EM Algorithm......Page 302 Gaussian Scale Mixtures......Page 304 Nonlocal Means......Page 308 Least Squares and Total Variation......Page 310 Constrained Least Squares......Page 311 Total Variation Method......Page 312 Image Superresolution......Page 313 Color Image Processing......Page 316 Conclusions......Page 317 Problems......Page 318 Probability Review......Page 321 Random Sequences......Page 323 Stationary Random Sequences......Page 324 Random Processes......Page 326 References......Page 327 Introduction......Page 330 DCT......Page 332 SWT......Page 334 DPCM......Page 335 Quantization......Page 336 Uniform Quantization......Page 338 Optimal MSE Quantization......Page 339 An SQ Design Algorithm......Page 341 Vector Quantization......Page 342 LBG Algorithm [2]......Page 344 Huffman Coding......Page 347 Arithmetic Coding......Page 348 ECSQ and ECVQ......Page 350 DCT Coder......Page 351 SWT Coder......Page 355 Multiresolution SWT Coding......Page 360 Fully Embedded SWT Coders......Page 363 Embedded Zerotree Wavelet (EZW) Coder......Page 364 EZW Algorithm......Page 365 Set Partitioning in Hierarchical Trees Coder......Page 366 SPIHT Coding Algorithm......Page 367 EZBC Coding Algorithm......Page 368 Context-Based AC in EZBC......Page 369 JPEG 2000......Page 370 Color Image Coding......Page 371 Directional Transforms......Page 373 Robustness Considerations......Page 376 Problems......Page 377 Information Measure......Page 380 Data Compression......Page 385 Asymptotic Equipartition Principle......Page 387 Continuous Sources......Page 388 Rate-Distortion Theory......Page 389 References......Page 392 3-D Signals and Systems......Page 394 Properties of 3-D Fourier Transform......Page 396 3-D Sampling and Reconstruction......Page 397 General 3-D Sampling......Page 399 Spatiotemporal Signal Processing......Page 400 Spatiotemporal Sampling......Page 401 Spatiotemporal Filters......Page 402 Intraframe Filtering......Page 403 Intraframe Wiener Filter......Page 404 Interframe Filtering......Page 405 Interframe Wiener Filter......Page 406 Spatiotemporal Markov Models......Page 407 Causal and Semicausal 3-D Field Sequences......Page 409 Reduced Update Spatiotemporal Kalman Filter......Page 410 Local State and Update Region......Page 411 Problems......Page 413 References......Page 414 Interframe Processing......Page 415 Motion Estimation and Motion Compensation......Page 421 Block-Matching Method......Page 423 Hierarchical Block Matching......Page 426 Overlapped Block Motion Compensation......Page 427 Optical Flow Methods......Page 429 Mesh-Based Methods......Page 430 Motion-Compensated Filtering......Page 434 MC-Wiener Filter......Page 435 MC-Kalman Filter......Page 436 Multimodel MC-RUKF......Page 437 Deinterlacing......Page 440 Bayesian Method for Estimating Motion......Page 447 Joint Motion Estimation and Segmentation......Page 450 Restoration of Degraded Video and Film......Page 453 A Bayesian Approach......Page 454 Super-Resolution of Video......Page 455 Demosaicing......Page 456 Problems......Page 459 Appendix: Digital Video Formats......Page 461 ITU 601 Digital SDTV (a.k.a. SMPTE D1 and D5)......Page 462 DCI Formats......Page 463 References......Page 464 Digital Video Compression......Page 467 Intraframe Coding......Page 468 M-JPEG Pseudo Algorithm......Page 469 DV Codec......Page 472 Intraframe SWT Coding......Page 474 M-JPEG 2000......Page 476 Generalizing 1-D DPCM to Interframe Coding......Page 477 MC Spatiotemporal Prediction......Page 478 MPEG 1......Page 480 MPEG 2—A "Generic Standard"......Page 482 The Missing MPEG 3—High-Definition Television......Page 484 Video Processing of MPEG-coded Bitstreams......Page 485 Interframe SWT Coders......Page 486 Motion-Compensated SWT Hybrid Coding......Page 487 3-D or Spatiotemporal Transform Coding......Page 489 Scalable Video Coders......Page 493 More on MCTF......Page 496 Covered Pixel Detection Algorithm......Page 497 Bidirectional MCTF......Page 498 Enhanced MC-EZBC......Page 502 Current Interframe Coding Standards......Page 503 H.264/AVC......Page 504 Video Coder Mode Control......Page 507 H.264/SVC......Page 508 SVC for Video Conferencing......Page 512 H.264/MVC......Page 515 Intra-Macroblock Displacement Compensation......Page 517 Template Matching for Intra Prediction......Page 518 Object-Based Coding......Page 519 Comments on the Sensitivity of Compressed Video......Page 522 Problems......Page 523 References......Page 525 Video on IP Networks......Page 529 Best-Efforts Network......Page 530 Layers and Protocol Stack......Page 531 TCP Friendly......Page 532 Reversible Variable Length Coding......Page 533 Multiple Description Coding......Page 534 Forward Error Control Coding......Page 535 Wireless Networks......Page 536 Joint Source-Channel Coding......Page 537 Error Concealment......Page 539 DP of Images......Page 540 DP of Video......Page 544 Multiple Description FEC......Page 545 Robust 3D-SPIHT......Page 548 A Robust MC-EZBC......Page 549 Error-Resilience Features of H.264/AVC......Page 550 Slice Interleaving and Flexible Macroblock Ordering......Page 551 Switching Frames......Page 552 Reference Frame Selection......Page 553 Error Concealment in H.264/AVC......Page 554 Digital Item Adaptation in MPEG 21......Page 555 Fine Grain Adaptive FEC......Page 556 Network Coding of Video......Page 562 Practical Network Coding......Page 564 PNC Together with MDC......Page 566 Problems......Page 568 References......Page 570 Index......Page 574 B......Page 575 C......Page 576 D......Page 577 E......Page 579 H......Page 580 I......Page 581 L......Page 583 M......Page 584 N......Page 585 P......Page 586 R......Page 587 S......Page 589 T......Page 592 W......Page 593 Z......Page 594 Multidimensional Signal, Image, and Video Processing and Coding gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. Multidimensional Signal, Image, and Video Processing and Coding also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing.yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: New appendices on random processes, information theory New coverage of image analysis – edge detection, linking, clustering, and segmentation Expanded coverage on image sensing and perception, including color spaces Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming New coverage of super-resolution methods for image and video Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected New chapters on introductory random processes, information theory, and image enhancement and analysis Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC) This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: New appendices on random processes, information theory New coverage of image analysis - edge detection, linking, clustering, and segmentation Expanded coverage on image sensing and perception, including color spaces. Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC. Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding. More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming. New coverage of super-resolution methods for image and video. Only R & D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected. New chapters on introductory random processes, information theory, and image enhancement and analysis Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC) 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. This fully revised and expanded second edition, will give you the necessary understanding of image and video processing concepts to contribute to this hot technology's future advances. Important new topics include introductory random processes, image enhancement and analysis, and the new MPEG scalable video coding standard. Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected. New chapters on introductory random processes, information theory, and image enhancement and analysis Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC) 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. This fully revised and expanded second edition, will give you the necessary understanding of image and video processing concepts to contribute to this hot technology's future advances. Important new topics include introductory random processes, image enhancement and analysis, and the new MPEG scalable video coding standard. Only R & D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected. New chapters on introductory random processes, information theory, and image enhancement and analysis Coverage and discussion of the latest standards in video coding : H.264/AVC and the new scalable video standard (SVC).--[Source inconnue]