MATLAB版数字图像处理（第二版）（英文版）

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数字图像处理（MATLAB版）（第二版）（英文版）本书集成了冈萨雷斯和伍兹所着的《数字图像处理（第三版）》一书中重要的原文材料和MathWorks公司的图像处理工具箱。本书的特色在于重点强调怎样通过开发新代码来加强这些软体工具。
【MATLAB版数字图像处理（第二版）（英文版）】本书在介绍MATLAB编程基础知识之后，讲述了图像处理的主干内容，包括灰度变换、线性和非线性空间滤波、频率域滤波、图像复原与重建、几何变换和图像配準、彩色图像处理、小波、图像压缩、形态学图像处理、图像分割、区域和边界表示与描述。
基本介绍书名：数字图像处理（MATLAB版）（第二版）（英文版）
ISBN：9787121195440
出版社：电子工业出版社
出版时间：2013-04-01
图书内容这是图像处理基础理论论述同以MATLAB为主要工具的软体实践方法相对照的第一本书。本书集成了冈萨雷斯和伍兹所着的《数字图像处理（第三版）》一书中重要的原文材料和MathWorks公司的图像处理工具箱。本书的特色在于重点强调怎样通过开发新代码来加强这些软体工具。本书在介绍MATLAB编程基础知识之后，讲述了图像处理的主干内容，包括灰度变换、线性和非线性空间滤波、频率域滤波、图像复原与重建、几何变换和图像配準、彩色图像处理、小波、图像压缩、形态学图像处理、图像分割、区域和边界表示与描述。目录ContentsPrefaceAcknowledgementsAbout the Authors1 IntroductionPreview1.1 Background1.2 What Is Digital Image Processing?1.3 Background on MATLAB and the Image Processing Toolbox1.4 Areas of Image Processing Covered in the Book1.5 The Book Web Site1.6 Notation1.7 Fundamentals1.7.1 The MATLAB Desktop1.7.2 Using the MATLAB Editor/Debugger1.7.3 Getting Help1.7.4 Saving and Retrieving Work Session Data1.7.5 Digital Image Representation1.7.6 Image I/O and Display1.7.7 Classes and Image Types1.7.8 M-Function Programming1.8 How References Are Organized in the BookSummary2 Intensity Transformations and Spatial FilteringPreview2.1 Background2.2 Intensity Transformation Functions2.2.1 Functions imadjust and stretchlim2.2.2 Logarithmic and Contrast- Stretching Transformations2.2.3 Specifying Arbitrary Intensity Transformations2.2.4 Some Utility M-functions for Intensity Transformations2.3 Histogram Processing and Function Plotting2.3.1 Generating and Plotting Image Histograms2.3.2 Histogram Equalization2.3.3 Histogram Matching (Specification)2.3.4 Function adapthisteq2.4 Spatial Filtering2.4.1 Linear Spatial Filtering2.4.2 Nonlinear Spatial Filtering2.5 Image Processing Toolbox Standard Spatial Filters2.5.1 Linear Spatial Filters2.5.2 Nonlinear Spatial Filters2.6 Using Fuzzy Techniques for Intensity Transformations and SpatialFiltering2.6.1 Background2.6.2 Introduction to Fuzzy Sets2.6.3 Using Fuzzy Sets2.6.4 A Set of Custom Fuzzy M-functions2.6.5 Using Fuzzy Sets for Intensity Transformations2.6.6 Using Fuzzy Sets for Spatial FilteringSummary3 Filtering in the Frequency DomainPreview3.1 The 2-D Discrete Fourier Transform3.2 Computing and Visualizing the 2-D DFT in MATLAB3.3 Filtering in the Frequency Domain3.3.1 Fundamentals3.3.2 Basic Steps in DFT Filtering3.3.3 An M-function for Filtering in the Frequency Domain3.4 Obtaining Frequency Domain Filters from Spatial Filters 3.5 Generating Filters Directly in the Frequency Domain3.5.1 Creating Meshgrid Arrays for Use in Implementing Filtersin the Frequency Domain3.5.2 Lowpass (Smoothing) Frequency Domain Filters3.5.3 Wireframe and Surface Plotting3.6 Highpass (Sharpening) Frequency Domain Filters3.6.1 A Function for Highpass Filtering3.6.2 High-Frequency Emphasis Filtering3.7 Selective Filtering3.7.1 Bandreject and Bandpass Filters3.7.2 Notchreject and Notchpass FiltersSummary4 Image Restoration and ReconstructionPreview4.1 A Model of the Image Degradation/Restoration Process4.2 Noise Models4.2.1 Adding Noise to Images with Function imnoise4.2.2 Generating Spatial Random Noise with a SpecifiedDistribution4.2.3 Periodic Noise4.2.4 Estimating Noise Parameters4.3 Restoration in the Presence of Noise Only—Spatial Filtering4.3.1 Spatial Noise Filters4.3.2 Adaptive Spatial Filters4.4 Periodic Noise Reduction Using Frequency Domain Filtering4.5 Modeling the Degradation Function4.6 Direct Inverse Filtering4.7 Wiener Filtering4.8 Constrained Least Squares (Regularized) Filtering4.9 Iterative Nonlinear Restoration Using the Lucy-RichardsonAlgorithm 4.10 Blind Deconvolution4.11 Image Reconstruction from Projections4.11.1 Background4.11.2 Parallel-Beam Projections and the Radon Transform4.11.3 The Fourier Slice Theorem and Filtered Backprojections4.11.4 Filter Implementation4.11.5 Reconstruction Using Fan-Beam Filtered Backprojections4.11.6 Function radon4.11.7 Function iradon4.11.8 Working with Fan-Beam DataSummary5 Geometric Transformations and ImageRegistrationPreview5.1 Transforming Points5.2 Affine Transformations5.3 Projective Transformations5.4 Applying Geometric Transformations to Images5.5 Image Coordinate Systems in MATLAB5.5.1 Output Image Location5.5.2 Controlling the Output Grid5.6 Image Interpolation5.6.1 Interpolation in Two Dimensions5.6.2 Comparing Interpolation Methods5.7 Image Registration5.7.1 Registration Process5.7.2 Manual Feature Selection and Matching Using cpselect5.7.3 Inferring Transformation Parameters Using cp2tform5.7.4 Visualizing Aligned Images5.7.5 Area-Based Registration5.7.6 Automatic Feature-Based RegistrationSummary6 Color Image ProcessingPreview6.1 Color Image Representation in MATLAB 6.1.1 RGB Images6.1.2 Indexed Images6.1.3 Functions for Manipulating RGB and Indexed Images6.2 Converting Between Color Spaces6.2.1 NTSC Color Space6.2.2 The YCbCr Color Space6.2.3 The HSV Color Space6.2.4 The CMY and CMYK Color Spaces6.2.5 The HSI Color Space6.2.6 Device-Independent Color Spaces6.3 The Basics of Color Image Processing6.4 Color Transformations6.5 Spatial Filtering of Color Images6.5.1 Color Image Smoothing6.5.2 Color Image Sharpening6.6 Working Directly in RGB Vector Space6.6.1 Color Edge Detection Using the Gradient6.6.2 Image Segmentation in RGB Vector SpaceSummary7 WaveletsPreview7.1 Background7.2 The Fast Wavelet Transform7.2.1 FWTs Using the Wavelet Toolbox7.2.2 FWTs without the Wavelet Toolbox7.3 Working with Wavelet Decomposition Structures7.3.1 Editing Wavelet Decomposition Coefficients without theWavelet Toolbox7.3.2 Displaying Wavelet Decomposition Coefficients7.4 The Inverse Fast Wavelet Transform7.5 Wavelets in Image ProcessingSummary8 Image CompressionPreview8.1 Background8.2 Coding Redundancy8.2.1 Huffman Codes8.2.2 Huffman Encoding 8.2.3 Huffman Decoding8.3 Spatial Redundancy8.4 Irrelevant Information8.5 JPEG Compression8.5.1 JPEG8.5.2 JPEG 20008.6 Video Compression8.6.1 MATLAB Image Sequences and Movies8.6.2 Temporal Redundancy and Motion CompensationSummary9 Morphological Image ProcessingPreview9.1 Preliminaries9.1.1 Some Basic Concepts from Set Theory9.1.2 Binary Images, Sets, and Logical Operators9.2 Dilation and Erosion9.2.1 Dilation9.2.2 Structuring Element Decomposition9.2.3 The strel Function9.2.4 Erosion9.3 Combining Dilation and Erosion9.3.1 Opening and Closing9.3.2 The Hit-or-Miss Transformation9.3.3 Using Lookup Tables9.3.4 Function bwmorph9.4 Labeling Connected Components9.5 Morphological Reconstruction9.5.1 Opening by Reconstruction9.5.2 Filling Holes9.5.3 Clearing Border Objects9.6 Gray-Scale Morphology9.6.1 Dilation and Erosion9.6.2 Opening and Closing9.6.3 ReconstructionSummary10 Image SegmentationPreview10.1 Point, Line, and Edge Detection10.1.1 Point Detection10.1.2 Line Detection10.1.3 Edge Detection Using Function edge10.2 Line Detection Using the Hough Transform 10.2.1 Background10.2.2 Toolbox Hough Functions10.3 Thresholding10.3.1 Foundation10.3.2 Basic Global Thresholding10.3.3 Optimum Global Thresholding Using Otsu's Method10.3.4 Using Image Smoothing to Improve Global Thresholding10.3.5 Using Edges to Improve Global Thresholding10.3.6 Variable Thresholding Based on Local Statistics10.3.7 Image Thresholding Using Moving Averages10.4 Region-Based Segmentation10.4.1 Basic Formulation10.4.2 Region Growing10.4.3 Region Splitting and Merging10.5 Segmentation Using the Watershed Transform10.5.1 Watershed Segmentation Using the Distance Transform10.5.2 Watershed Segmentation Using Gradients10.5.3 Marker-Controlled Watershed SegmentationSummary11 Representation and DescriptionPreview11.1 Background11.1.1 Functions for Extracting Regions and Their Boundaries11.1.2 Some Additional MATLAB and Toolbox Functions Usedin This Chapter11.1.3 Some Basic Utility M-Functions11.2 Representation11.2.1 Chain Codes11.2.2 Polygonal Approximations Using Minimum-Perimeter Polygons11.2.3 Signatures11.2.4 Boundary Segments11.2.5 Skeletons11.3 Boundary Descriptors11.3.1 Some Simple Descriptors11.3.2 Shape Numbers11.3.3 Fourier Descriptors 11.3.4 Statistical Moments11.3.5 Corners11.4 Regional Descriptors11.4.1 Function regionprops11.4.2 Texture11.4.3 Moment Invariants11.5 Using Principal Components for DescriptionSummaryAppendix A M-Function SummaryAppendix B ICE and MATLAB Graphical User InterfacesAppendix C Additional Custom M-functionsBibliographyIndex

MATLAB版 数字图像处理（第二版）（英文版）

MATLAB版数字图像处理（第二版）（英文版）