Digital Image Interpolation in Matlab

Inbunden, Engelska, 2019

1 979 kr

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This book provides a comprehensive study in digital image interpolation with theoretical, analytical and Matlab® implementation. It includes all historically and practically important interpolation algorithms, accompanied with Matlab® source code on a website, which will assist readers to learn and understand the implementation details of each presented interpolation algorithm. Furthermore, sections in fundamental signal processing theories and image quality models are also included. The authors intend for the book to help readers develop a thorough consideration of the design of image interpolation algorithms and applications for their future research in the field of digital image processing. Introduces a wide range of traditional and advanced image interpolation methods concisely and provides thorough treatment of theoretical foundationsDiscusses in detail the assumptions and limitations of presented algorithmsInvestigates a variety of interpolation and implementation methods including transform domain, edge-directed, wavelet and scale-space, and fractal based methodsFeatures simulation results for comparative analysis, summaries and computational and analytical exercises at the end of each chapterDigital Image Interpolation in Matlab® is an excellent guide for researchers and engineers working in digital imaging and digital video technologies. Graduate students studying digital image processing will also benefit from this practical reference text.

Produktinformation

Utgivningsdatum2019-02-26
Mått175 x 246 x 23 mm
Vikt680 g
FormatInbunden
SpråkEngelska
SerieIEEE Press
Antal sidor336
FörlagJohn Wiley & Sons Inc
ISBN9781119119616

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About the Authors xiiiPreface xvAcknowledgments xixNomenclature xxiAbbreviations xxiiiAbout the CompanionWebsite xxv1 Signal Sampling 11.1 Sampling and Bandlimited Signal 11.2 Unitary Transform 41.2.1 Discrete Fourier Transform 41.3 Quantization 51.3.1 Quantization and Sampling Interaction 71.4 Sampled Function Approximation: Fitting and Interpolation 81.4.1 Zero-Order Hold (ZOH) 101.4.2 First-Order Hold (FOH) 101.4.3 Digital Interpolation 121.5 Book Organization 121.6 Exercises 152 Digital Image 172.1 Digital Imaging in MATLAB 212.2 Current Pixel and Neighboring Pixels 232.3 Frequency Domain 242.3.1 Transform Kernel 282.4 2D Filtering 282.4.1 Boundary Extension and Cropping 302.4.1.1 Constant Extension 312.4.1.2 Periodic Extension 312.4.1.3 Symmetric Extension 322.4.1.4 Infinite Extension 322.4.1.5 Cropping 332.5 Edge Extraction 342.5.1 First-Order Derivative Edge Detection Operators 362.5.1.1 Sobel Operator 372.5.2 Second-Order Derivative and Zero-Crossing Edge Detector 402.5.2.1 Laplacian Operator 412.5.2.2 Gaussian Smoothing 422.6 Geometric Transformation 452.6.1 Translation 462.6.2 Reflection 472.6.3 Scaling 472.6.4 Rotation 492.6.5 Affine Transformation 502.7 Resize an Image 512.7.1 Interpolation 512.7.2 Decimation 542.7.2.1 Direct Subsampling 552.7.2.2 Sinc Filter 552.7.2.3 Block Averaging 562.7.3 Built-in Image Resizing Function in MATLAB 572.8 Color Image 582.8.1 Color Filter Array and Demosaicing 602.8.2 Perceptual Color Space 602.9 Noise 622.9.1 Rank Order Filtering 652.9.2 Smoothing Filtering 652.10 Summary 672.11 Exercises 673 Image Quality 713.1 Image Features and Artifacts 723.1.1 Aliasing (Jaggy) 733.1.2 Smoothing (Blurring) 743.1.3 Edge Halo 743.1.4 Ringing 753.1.5 Blocking 753.2 Objective Quality Measure 753.2.1 Mean Squares Error 773.2.2 Peak Signal-to-Noise Ratio 783.2.3 Edge PSNR 793.3 Structural Similarity 813.3.1 Luminance 833.3.2 Contrast 843.3.3 Structural 843.3.4 Sensitivity of SSIM 853.3.4.1 K1 Sensitivity 853.3.4.2 K2 Sensitivity 863.4 Summary 883.5 Exercises 884 Nonadaptive Interpolation 914.1 Image Interpolation: Overture 924.1.1 Interpolation Kernel Characteristics 944.1.2 Nearest Neighbor 944.1.3 Bilinear 984.1.4 Bicubic 1034.2 Frequency Domain Analysis 1104.3 Mystery of Order 1114.4 Application: Affine Transformation 1134.4.1 Structural Integrity 1164.5 Summary 1184.6 Exercises 1205 Transform Domain 1235.1 DFT Zero Padding Interpolation 1255.1.1 Implementation 1275.2 Discrete Cosine Transform 1325.2.1 DCT Zero Padding Interpolation 1345.3 DCT Zero Padding Image Interpolation 1385.3.1 Blocked Transform 1385.3.2 Block-Based DCT Zero Padding Interpolation 1405.3.2.1 Does Kernel Size Matter 1425.4 Overlapping 1445.5 Multi-Kernels 1495.5.1 Extendible Inverse DCT 1495.6 Iterative Error Correction 1525.7 Summary 1565.8 Exercises 1576 Wavelet 1616.1 Wavelet Analysis 1626.1.1 Perfect Reconstruction 1636.1.2 Multi-resolution Analysis 1646.1.3 2DWavelet Transform 1666.2 Wavelet Image Interpolation 1686.2.1 Zero Padding 1686.2.2 Multi-resolution Subband Image Estimation 1706.2.3 Hölder Regularity 1766.2.3.1 Local Regularity-Preserving Problems 1776.3 Cycle Spinning 1796.3.1 Zero Padding (WZP-CS) 1796.3.2 High Frequency Subband Estimation (WLR-CS) 1816.4 Error Correction 1846.5 WhichWavelets to Use 1866.6 Summary 1876.7 Exercises 1887 Edge-Directed Interpolation 1917.1 Explicit Edge-Directed Interpolation 1937.2 Implicit Edge-Directed Interpolation 1967.2.1 Canny Edge Interpolation (CEI) 1977.2.2 Edge-Based Line Averaging (ELA) 1987.2.3 Directional-Orientation Interpolation (DOI) 1997.2.4 Error-Amended Sharp Edge (EASE) 2017.3 Summary 2087.4 Exercises 2098 Covariance-Based Interpolation 2118.1 Modeling of Image Features 2128.2 Interpolation by Autoregression 2138.3 New Edge-Directed Interpolation (NEDI) 2158.3.1 Type 0 Estimation 2208.3.2 Type 1 Estimation 2228.3.3 Type 2 Estimation 2238.3.4 Pixel Intensity Correction 2258.3.5 MATLAB Implementation 2268.4 Boundary Extension 2288.5 Threshold Selection 2318.6 Error PropagationMitigation 2338.7 CovarianceWindow Adaptation 2388.7.1 PredictionWindow Adaptation 2398.7.2 Mean CovarianceWindow Adaptation 2418.7.3 Enhanced Modified Edge-Directed Interpolation (EMEDI) 2428.8 Iterative Covariance Correction 2498.8.1 iMEDI Implementation 2558.9 Summary 2608.10 Exercises 2619 Partitioned Fractal Interpolation 2639.1 Iterated Function System 2649.1.1 Banach Fixed-Point Theorem 2649.2 Partitioned Iterative Function System 2669.3 Encoding 2699.3.1 Range Block Partition 2699.3.2 Domain Block Partition 2709.3.3 Codebook Generation 2719.3.4 Grayscale Scaling 2749.3.5 Fractal Encoding Implementation 2769.4 Decoding 2779.4.1 Does Size Matter 2819.5 Decoding with Interpolation 2839.5.1 From Fitting to Interpolation 2859.6 Overlapping 2879.7 Summary 2899.8 Exercises 290Appendix MATLAB Functions List 291Bibliography 295Index 299