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Digital image interpolation in Matlab / Dr. Chi-Wah Kok, Canaan Microelectronics Corp Ltd., Hong Kong, CH, Dr. Wing-Shan Tam, Canaan Microelectronics Corp Ltd., Hong Kong, CH.

By: Kok, Chi-Wah [author.].
Contributor(s): Tam, Wing-Shan [author.] | IEEE Xplore (Online Service) [distributor.] | Wiley [publisher.].
Material type: materialTypeLabelBookPublisher: Hoboken, New Jersey : John Wiley & Sons, Inc., 2019Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2018]Edition: First edition.Description: 1 PDF (336 pages).Content type: text Media type: electronic Carrier type: online resourceISBN: 9781119119623.Subject(s): MATLAB | Image processing -- Digital techniques -- Data processing | InterpolationGenre/Form: Electronic books.DDC classification: 006.6/86 Online resources: Abstract with links to resource Also available in print.
Contents:
About the Authors xiii -- Preface xv -- Acknowledgments xix -- Nomenclature xxi -- Abbreviations xxiii -- About the CompanionWebsite xxv -- 1 Signal Sampling 1 -- 1.1 Sampling and Bandlimited Signal 1 -- 1.2 Unitary Transform 4 -- 1.2.1 Discrete Fourier Transform 4 -- 1.3 Quantization 5 -- 1.3.1 Quantization and Sampling Interaction 7 -- 1.4 Sampled Function Approximation: Fitting and Interpolation 8 -- 1.4.1 Zero-Order Hold (ZOH) 10 -- 1.4.2 First-Order Hold (FOH) 10 -- 1.4.3 Digital Interpolation 12 -- 1.5 Book Organization 12 -- 1.6 Exercises 15 -- 2 Digital Image 17 -- 2.1 Digital Imaging in MATLAB 21 -- 2.2 Current Pixel and Neighboring Pixels 23 -- 2.3 Frequency Domain 24 -- 2.3.1 Transform Kernel 28 -- 2.4 2D Filtering 28 -- 2.4.1 Boundary Extension and Cropping 30 -- 2.4.1.1 Constant Extension 31 -- 2.4.1.2 Periodic Extension 31 -- 2.4.1.3 Symmetric Extension 32 -- 2.4.1.4 Infinite Extension 32 -- 2.4.1.5 Cropping 33 -- 2.5 Edge Extraction 34 -- 2.5.1 First-Order Derivative Edge Detection Operators 36 -- 2.5.1.1 Sobel Operator 37 -- 2.5.2 Second-Order Derivative and Zero-Crossing Edge Detector 40 -- 2.5.2.1 Laplacian Operator 41 -- 2.5.2.2 Gaussian Smoothing 42 -- 2.6 Geometric Transformation 45 -- 2.6.1 Translation 46 -- 2.6.2 Reflection 47 -- 2.6.3 Scaling 47 -- 2.6.4 Rotation 49 -- 2.6.5 Affine Transformation 50 -- 2.7 Resize an Image 51 -- 2.7.1 Interpolation 51 -- 2.7.2 Decimation 54 -- 2.7.2.1 Direct Subsampling 55 -- 2.7.2.2 Sinc Filter 55 -- 2.7.2.3 Block Averaging 56 -- 2.7.3 Built-in Image Resizing Function in MATLAB 57 -- 2.8 Color Image 58 -- 2.8.1 Color Filter Array and Demosaicing 60 -- 2.8.2 Perceptual Color Space 60 -- 2.9 Noise 62 -- 2.9.1 Rank Order Filtering 65 -- 2.9.2 Smoothing Filtering 65 -- 2.10 Summary 67 -- 2.11 Exercises 67 -- 3 Image Quality 71 -- 3.1 Image Features and Artifacts 72 -- 3.1.1 Aliasing (Jaggy) 73 -- 3.1.2 Smoothing (Blurring) 74 -- 3.1.3 Edge Halo 74 -- 3.1.4 Ringing 75 -- 3.1.5 Blocking 75 -- 3.2 Objective Quality Measure 75.
3.2.1 Mean Squares Error 77 -- 3.2.2 Peak Signal-to-Noise Ratio 78 -- 3.2.3 Edge PSNR 79 -- 3.3 Structural Similarity 81 -- 3.3.1 Luminance 83 -- 3.3.2 Contrast 84 -- 3.3.3 Structural 84 -- 3.3.4 Sensitivity of SSIM 85 -- 3.3.4.1 K1 Sensitivity 85 -- 3.3.4.2 K2 Sensitivity 86 -- 3.4 Summary 88 -- 3.5 Exercises 88 -- 4 Nonadaptive Interpolation 91 -- 4.1 Image Interpolation: Overture 92 -- 4.1.1 Interpolation Kernel Characteristics 94 -- 4.1.2 Nearest Neighbor 94 -- 4.1.3 Bilinear 98 -- 4.1.4 Bicubic 103 -- 4.2 Frequency Domain Analysis 110 -- 4.3 Mystery of Order 111 -- 4.4 Application: Affine Transformation 113 -- 4.4.1 Structural Integrity 116 -- 4.5 Summary 118 -- 4.6 Exercises 120 -- 5 Transform Domain 123 -- 5.1 DFT Zero Padding Interpolation 125 -- 5.1.1 Implementation 127 -- 5.2 Discrete Cosine Transform 132 -- 5.2.1 DCT Zero Padding Interpolation 134 -- 5.3 DCT Zero Padding Image Interpolation 138 -- 5.3.1 Blocked Transform 138 -- 5.3.2 Block-Based DCT Zero Padding Interpolation 140 -- 5.3.2.1 Does Kernel Size Matter 142 -- 5.4 Overlapping 144 -- 5.5 Multi-Kernels 149 -- 5.5.1 Extendible Inverse DCT 149 -- 5.6 Iterative Error Correction 152 -- 5.7 Summary 156 -- 5.8 Exercises 157 -- 6 Wavelet 161 -- 6.1 Wavelet Analysis 162 -- 6.1.1 Perfect Reconstruction 163 -- 6.1.2 Multi-resolution Analysis 164 -- 6.1.3 2DWavelet Transform 166 -- 6.2 Wavelet Image Interpolation 168 -- 6.2.1 Zero Padding 168 -- 6.2.2 Multi-resolution Subband Image Estimation 170 -- 6.2.3 Hölder Regularity 176 -- 6.2.3.1 Local Regularity-Preserving Problems 177 -- 6.3 Cycle Spinning 179 -- 6.3.1 Zero Padding (WZP-CS) 179 -- 6.3.2 High Frequency Subband Estimation (WLR-CS) 181 -- 6.4 Error Correction 184 -- 6.5 WhichWavelets to Use 186 -- 6.6 Summary 187 -- 6.7 Exercises 188 -- 7 Edge-Directed Interpolation 191 -- 7.1 Explicit Edge-Directed Interpolation 193 -- 7.2 Implicit Edge-Directed Interpolation 196 -- 7.2.1 Canny Edge Interpolation (CEI) 197 -- 7.2.2 Edge-Based Line Averaging (ELA) 198.
7.2.3 Directional-Orientation Interpolation (DOI) 199 -- 7.2.4 Error-Amended Sharp Edge (EASE) 201 -- 7.3 Summary 208 -- 7.4 Exercises 209 -- 8 Covariance-Based Interpolation 211 -- 8.1 Modeling of Image Features 212 -- 8.2 Interpolation by Autoregression 213 -- 8.3 New Edge-Directed Interpolation (NEDI) 215 -- 8.3.1 Type 0 Estimation 220 -- 8.3.2 Type 1 Estimation 222 -- 8.3.3 Type 2 Estimation 223 -- 8.3.4 Pixel Intensity Correction 225 -- 8.3.5 MATLAB Implementation 226 -- 8.4 Boundary Extension 228 -- 8.5 Threshold Selection 231 -- 8.6 Error PropagationMitigation 233 -- 8.7 CovarianceWindow Adaptation 238 -- 8.7.1 PredictionWindow Adaptation 239 -- 8.7.2 Mean CovarianceWindow Adaptation 241 -- 8.7.3 Enhanced Modified Edge-Directed Interpolation (EMEDI) 242 -- 8.8 Iterative Covariance Correction 249 -- 8.8.1 iMEDI Implementation 255 -- 8.9 Summary 260 -- 8.10 Exercises 261 -- 9 Partitioned Fractal Interpolation 263 -- 9.1 Iterated Function System 264 -- 9.1.1 Banach Fixed-Point Theorem 264 -- 9.2 Partitioned Iterative Function System 266 -- 9.3 Encoding 269 -- 9.3.1 Range Block Partition 269 -- 9.3.2 Domain Block Partition 270 -- 9.3.3 Codebook Generation 271 -- 9.3.4 Grayscale Scaling 274 -- 9.3.5 Fractal Encoding Implementation 276 -- 9.4 Decoding 277 -- 9.4.1 Does Size Matter 281 -- 9.5 Decoding with Interpolation 283 -- 9.5.1 From Fitting to Interpolation 285 -- 9.6 Overlapping 287 -- 9.7 Summary 289 -- 9.8 Exercises 290 -- Appendix MATLAB Functions List 291 -- Bibliography 295 -- Index 299.
Summary: "Provides a comprehensive explanation of digital image interpolation - Logical and well-planned organization with easy to follow examples - An excellent reference for all digital image processing courses, in both computer science and electrical and computer engineering departments - Accompanying website includes Matlab source code to assist better learning and understanding of the algorithms Market description (Please include secondary markets) Tier C/P&R Primary: Researchers and engineers working in digital image and digital video Secondary: Graduate students studying digital image processing"-- Provided by publisher.
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Includes bibliographical references and index.

About the Authors xiii -- Preface xv -- Acknowledgments xix -- Nomenclature xxi -- Abbreviations xxiii -- About the CompanionWebsite xxv -- 1 Signal Sampling 1 -- 1.1 Sampling and Bandlimited Signal 1 -- 1.2 Unitary Transform 4 -- 1.2.1 Discrete Fourier Transform 4 -- 1.3 Quantization 5 -- 1.3.1 Quantization and Sampling Interaction 7 -- 1.4 Sampled Function Approximation: Fitting and Interpolation 8 -- 1.4.1 Zero-Order Hold (ZOH) 10 -- 1.4.2 First-Order Hold (FOH) 10 -- 1.4.3 Digital Interpolation 12 -- 1.5 Book Organization 12 -- 1.6 Exercises 15 -- 2 Digital Image 17 -- 2.1 Digital Imaging in MATLAB 21 -- 2.2 Current Pixel and Neighboring Pixels 23 -- 2.3 Frequency Domain 24 -- 2.3.1 Transform Kernel 28 -- 2.4 2D Filtering 28 -- 2.4.1 Boundary Extension and Cropping 30 -- 2.4.1.1 Constant Extension 31 -- 2.4.1.2 Periodic Extension 31 -- 2.4.1.3 Symmetric Extension 32 -- 2.4.1.4 Infinite Extension 32 -- 2.4.1.5 Cropping 33 -- 2.5 Edge Extraction 34 -- 2.5.1 First-Order Derivative Edge Detection Operators 36 -- 2.5.1.1 Sobel Operator 37 -- 2.5.2 Second-Order Derivative and Zero-Crossing Edge Detector 40 -- 2.5.2.1 Laplacian Operator 41 -- 2.5.2.2 Gaussian Smoothing 42 -- 2.6 Geometric Transformation 45 -- 2.6.1 Translation 46 -- 2.6.2 Reflection 47 -- 2.6.3 Scaling 47 -- 2.6.4 Rotation 49 -- 2.6.5 Affine Transformation 50 -- 2.7 Resize an Image 51 -- 2.7.1 Interpolation 51 -- 2.7.2 Decimation 54 -- 2.7.2.1 Direct Subsampling 55 -- 2.7.2.2 Sinc Filter 55 -- 2.7.2.3 Block Averaging 56 -- 2.7.3 Built-in Image Resizing Function in MATLAB 57 -- 2.8 Color Image 58 -- 2.8.1 Color Filter Array and Demosaicing 60 -- 2.8.2 Perceptual Color Space 60 -- 2.9 Noise 62 -- 2.9.1 Rank Order Filtering 65 -- 2.9.2 Smoothing Filtering 65 -- 2.10 Summary 67 -- 2.11 Exercises 67 -- 3 Image Quality 71 -- 3.1 Image Features and Artifacts 72 -- 3.1.1 Aliasing (Jaggy) 73 -- 3.1.2 Smoothing (Blurring) 74 -- 3.1.3 Edge Halo 74 -- 3.1.4 Ringing 75 -- 3.1.5 Blocking 75 -- 3.2 Objective Quality Measure 75.

3.2.1 Mean Squares Error 77 -- 3.2.2 Peak Signal-to-Noise Ratio 78 -- 3.2.3 Edge PSNR 79 -- 3.3 Structural Similarity 81 -- 3.3.1 Luminance 83 -- 3.3.2 Contrast 84 -- 3.3.3 Structural 84 -- 3.3.4 Sensitivity of SSIM 85 -- 3.3.4.1 K1 Sensitivity 85 -- 3.3.4.2 K2 Sensitivity 86 -- 3.4 Summary 88 -- 3.5 Exercises 88 -- 4 Nonadaptive Interpolation 91 -- 4.1 Image Interpolation: Overture 92 -- 4.1.1 Interpolation Kernel Characteristics 94 -- 4.1.2 Nearest Neighbor 94 -- 4.1.3 Bilinear 98 -- 4.1.4 Bicubic 103 -- 4.2 Frequency Domain Analysis 110 -- 4.3 Mystery of Order 111 -- 4.4 Application: Affine Transformation 113 -- 4.4.1 Structural Integrity 116 -- 4.5 Summary 118 -- 4.6 Exercises 120 -- 5 Transform Domain 123 -- 5.1 DFT Zero Padding Interpolation 125 -- 5.1.1 Implementation 127 -- 5.2 Discrete Cosine Transform 132 -- 5.2.1 DCT Zero Padding Interpolation 134 -- 5.3 DCT Zero Padding Image Interpolation 138 -- 5.3.1 Blocked Transform 138 -- 5.3.2 Block-Based DCT Zero Padding Interpolation 140 -- 5.3.2.1 Does Kernel Size Matter 142 -- 5.4 Overlapping 144 -- 5.5 Multi-Kernels 149 -- 5.5.1 Extendible Inverse DCT 149 -- 5.6 Iterative Error Correction 152 -- 5.7 Summary 156 -- 5.8 Exercises 157 -- 6 Wavelet 161 -- 6.1 Wavelet Analysis 162 -- 6.1.1 Perfect Reconstruction 163 -- 6.1.2 Multi-resolution Analysis 164 -- 6.1.3 2DWavelet Transform 166 -- 6.2 Wavelet Image Interpolation 168 -- 6.2.1 Zero Padding 168 -- 6.2.2 Multi-resolution Subband Image Estimation 170 -- 6.2.3 Hölder Regularity 176 -- 6.2.3.1 Local Regularity-Preserving Problems 177 -- 6.3 Cycle Spinning 179 -- 6.3.1 Zero Padding (WZP-CS) 179 -- 6.3.2 High Frequency Subband Estimation (WLR-CS) 181 -- 6.4 Error Correction 184 -- 6.5 WhichWavelets to Use 186 -- 6.6 Summary 187 -- 6.7 Exercises 188 -- 7 Edge-Directed Interpolation 191 -- 7.1 Explicit Edge-Directed Interpolation 193 -- 7.2 Implicit Edge-Directed Interpolation 196 -- 7.2.1 Canny Edge Interpolation (CEI) 197 -- 7.2.2 Edge-Based Line Averaging (ELA) 198.

7.2.3 Directional-Orientation Interpolation (DOI) 199 -- 7.2.4 Error-Amended Sharp Edge (EASE) 201 -- 7.3 Summary 208 -- 7.4 Exercises 209 -- 8 Covariance-Based Interpolation 211 -- 8.1 Modeling of Image Features 212 -- 8.2 Interpolation by Autoregression 213 -- 8.3 New Edge-Directed Interpolation (NEDI) 215 -- 8.3.1 Type 0 Estimation 220 -- 8.3.2 Type 1 Estimation 222 -- 8.3.3 Type 2 Estimation 223 -- 8.3.4 Pixel Intensity Correction 225 -- 8.3.5 MATLAB Implementation 226 -- 8.4 Boundary Extension 228 -- 8.5 Threshold Selection 231 -- 8.6 Error PropagationMitigation 233 -- 8.7 CovarianceWindow Adaptation 238 -- 8.7.1 PredictionWindow Adaptation 239 -- 8.7.2 Mean CovarianceWindow Adaptation 241 -- 8.7.3 Enhanced Modified Edge-Directed Interpolation (EMEDI) 242 -- 8.8 Iterative Covariance Correction 249 -- 8.8.1 iMEDI Implementation 255 -- 8.9 Summary 260 -- 8.10 Exercises 261 -- 9 Partitioned Fractal Interpolation 263 -- 9.1 Iterated Function System 264 -- 9.1.1 Banach Fixed-Point Theorem 264 -- 9.2 Partitioned Iterative Function System 266 -- 9.3 Encoding 269 -- 9.3.1 Range Block Partition 269 -- 9.3.2 Domain Block Partition 270 -- 9.3.3 Codebook Generation 271 -- 9.3.4 Grayscale Scaling 274 -- 9.3.5 Fractal Encoding Implementation 276 -- 9.4 Decoding 277 -- 9.4.1 Does Size Matter 281 -- 9.5 Decoding with Interpolation 283 -- 9.5.1 From Fitting to Interpolation 285 -- 9.6 Overlapping 287 -- 9.7 Summary 289 -- 9.8 Exercises 290 -- Appendix MATLAB Functions List 291 -- Bibliography 295 -- Index 299.

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"Provides a comprehensive explanation of digital image interpolation - Logical and well-planned organization with easy to follow examples - An excellent reference for all digital image processing courses, in both computer science and electrical and computer engineering departments - Accompanying website includes Matlab source code to assist better learning and understanding of the algorithms Market description (Please include secondary markets) Tier C/P&R Primary: Researchers and engineers working in digital image and digital video Secondary: Graduate students studying digital image processing"-- Provided by publisher.

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