Digital image processing using MATLAB

副标题:无

作   者:(美)Rafael C. Gonzalez,(美)Richard E. Woods,(美)Steven L. Eddins著

分类号:

ISBN:9787121195440

微信扫一扫,移动浏览光盘

简介

这是图像处理基础理论论述同以MATLAB为主要工具的软件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著的《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件工具。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、几何变换和图像配准、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

Contents
Preface
Acknowledgements
About the Authors
1 Introduction
 Preview
 1.1 Background
 1.2 What Is Digital Image Processing?
 1.3 Background on MATLAB and the Image Processing Toolbox
 1.4 Areas of Image Processing Covered in the Book
 1.5 The Book Web Site
 1.6 Notation
 1.7 Fundamentals
 1.7.1 The MATLAB Desktop
 1.7.2 Using the MATLAB Editor/Debugger
 1.7.3 Getting Help
 1.7.4 Saving and Retrieving Work Session Data
 1.7.5 Digital Image Representation
 1.7.6 Image I/O and Display
 1.7.7 Classes and Image Types
 1.7.8 M-Function Programming
 1.8 How References Are Organized in the Book
 Summary
2 Intensity Transformations and Spatial Filtering
 Preview
 2.1 Background
 2.2 Intensity Transformation Functions
 2.2.1 Functions imadjust and stretchlim
 2.2.2 Logarithmic and Contrast- Stretching Transformations
 2.2.3 Specifying Arbitrary Intensity Transformations
 2.2.4 Some Utility M-functions for Intensity Transformations
 2.3 Histogram Processing and Function Plotting
 2.3.1 Generating and Plotting Image Histograms
 2.3.2 Histogram Equalization
 2.3.3 Histogram Matching (Specification)
 2.3.4 Function adapthisteq
 2.4 Spatial Filtering
 2.4.1 Linear Spatial Filtering
 2.4.2 Nonlinear Spatial Filtering
 2.5 Image Processing Toolbox Standard Spatial Filters
 2.5.1 Linear Spatial Filters
 2.5.2 Nonlinear Spatial Filters
 2.6 Using Fuzzy Techniques for Intensity Transformations and
Spatial
 Filtering
 2.6.1 Background
 2.6.2 Introduction to Fuzzy Sets
 2.6.3 Using Fuzzy Sets
 2.6.4 A Set of Custom Fuzzy M-functions
 2.6.5 Using Fuzzy Sets for Intensity Transformations
 2.6.6 Using Fuzzy Sets for Spatial Filtering
 Summary
3 Filtering in the Frequency Domain
 Preview
 3.1 The 2-D Discrete Fourier Transform
 3.2 Computing and Visualizing the 2-D DFT in MATLAB
 3.3 Filtering in the Frequency Domain
 3.3.1 Fundamentals
 3.3.2 Basic Steps in DFT Filtering
 3.3.3 An M-function for Filtering in the Frequency Domain
 3.4 Obtaining Frequency Domain Filters from Spatial Filters
 3.5 Generating Filters Directly in the Frequency Domain
 3.5.1 Creating Meshgrid Arrays for Use in Implementing
Filters
 in the Frequency Domain
 3.5.2 Lowpass (Smoothing) Frequency Domain Filters
 3.5.3 Wireframe and Surface Plotting
 3.6 Highpass (Sharpening) Frequency Domain Filters
 3.6.1 A Function for Highpass Filtering
 3.6.2 High-Frequency Emphasis Filtering
 3.7 Selective Filtering
 3.7.1 Bandreject and Bandpass Filters
 3.7.2 Notchreject and Notchpass Filters
 Summary
4 Image Restoration and Reconstruction
 Preview
 4.1 A Model of the Image Degradation/Restoration Process
 4.2 Noise Models
 4.2.1 Adding Noise to Images with Function imnoise
 4.2.2 Generating Spatial Random Noise with a Specified
 Distribution
 4.2.3 Periodic Noise
 4.2.4 Estimating Noise Parameters
 4.3 Restoration in the Presence of Noise Only—Spatial
Filtering
 4.3.1 Spatial Noise Filters
 4.3.2 Adaptive Spatial Filters
 4.4 Periodic Noise Reduction Using Frequency Domain
Filtering
 4.5 Modeling the Degradation Function
 4.6 Direct Inverse Filtering
 4.7 Wiener Filtering
 4.8 Constrained Least Squares (Regularized) Filtering
 4.9 Iterative Nonlinear Restoration Using the
Lucy-Richardson
 Algorithm
 4.10 Blind Deconvolution
 4.11 Image Reconstruction from Projections
 4.11.1 Background
 4.11.2 Parallel-Beam Projections and the Radon Transform
 4.11.3 The Fourier Slice Theorem and Filtered
Backprojections
 4.11.4 Filter Implementation
 4.11.5 Reconstruction Using Fan-Beam Filtered
Backprojections
 4.11.6 Function radon
 4.11.7 Function iradon
 4.11.8 Working with Fan-Beam Data
 Summary
5 Geometric Transformations and Image
 Registration
 Preview
 5.1 Transforming Points
 5.2 Affine Transformations
 5.3 Projective Transformations
 5.4 Applying Geometric Transformations to Images
 5.5 Image Coordinate Systems in MATLAB
 5.5.1 Output Image Location
 5.5.2 Controlling the Output Grid
 5.6 Image Interpolation
 5.6.1 Interpolation in Two Dimensions
 5.6.2 Comparing Interpolation Methods
 5.7 Image Registration
 5.7.1 Registration Process
 5.7.2 Manual Feature Selection and Matching Using cpselect
 5.7.3 Inferring Transformation Parameters Using cp2tform
 5.7.4 Visualizing Aligned Images
 5.7.5 Area-Based Registration
 5.7.6 Automatic Feature-Based Registration
 Summary
6 Color Image Processing
 Preview
 6.1 Color Image Representation in MATLAB
 6.1.1 RGB Images
 6.1.2 Indexed Images
 6.1.3 Functions for Manipulating RGB and Indexed Images
 6.2 Converting Between Color Spaces
 6.2.1 NTSC Color Space
 6.2.2 The YCbCr Color Space
 6.2.3 The HSV Color Space
 6.2.4 The CMY and CMYK Color Spaces
 6.2.5 The HSI Color Space
 6.2.6 Device-Independent Color Spaces
 6.3 The Basics of Color Image Processing
 6.4 Color Transformations
 6.5 Spatial Filtering of Color Images
 6.5.1 Color Image Smoothing
 6.5.2 Color Image Sharpening
 6.6 Working Directly in RGB Vector Space
 6.6.1 Color Edge Detection Using the Gradient
 6.6.2 Image Segmentation in RGB Vector Space
 Summary
7 Wavelets
 Preview
 7.1 Background
 7.2 The Fast Wavelet Transform
 7.2.1 FWTs Using the Wavelet Toolbox
 7.2.2 FWTs without the Wavelet Toolbox
 7.3 Working with Wavelet Decomposition Structures
 7.3.1 Editing Wavelet Decomposition Coefficients without the
 Wavelet Toolbox
 7.3.2 Displaying Wavelet Decomposition Coefficients
 7.4 The Inverse Fast Wavelet Transform
 7.5 Wavelets in Image Processing
 Summary
8 Image Compression
 Preview
 8.1 Background
 8.2 Coding Redundancy
 8.2.1 Huffman Codes
 8.2.2 Huffman Encoding
 8.2.3 Huffman Decoding
 8.3 Spatial Redundancy
 8.4 Irrelevant Information
 8.5 JPEG Compression
 8.5.1 JPEG
 8.5.2 JPEG 2000
 8.6 Video Compression
 8.6.1 MATLAB Image Sequences and Movies
 8.6.2 Temporal Redundancy and Motion Compensation
 Summary
9 Morphological Image Processing
 Preview
 9.1 Preliminaries
 9.1.1 Some Basic Concepts from Set Theory
 9.1.2 Binary Images, Sets, and Logical Operators
 9.2 Dilation and Erosion
 9.2.1 Dilation
 9.2.2 Structuring Element Decomposition
 9.2.3 The strel Function
 9.2.4 Erosion
 9.3 Combining Dilation and Erosion
 9.3.1 Opening and Closing
 9.3.2 The Hit-or-Miss Transformation
 9.3.3 Using Lookup Tables
 9.3.4 Function bwmorph
 9.4 Labeling Connected Components
 9.5 Morphological Reconstruction
 9.5.1 Opening by Reconstruction
 9.5.2 Filling Holes
 9.5.3 Clearing Border Objects
 9.6 Gray-Scale Morphology
 9.6.1 Dilation and Erosion
 9.6.2 Opening and Closing
 9.6.3 Reconstruction
 Summary
10 Image Segmentation
 Preview
 10.1 Point, Line, and Edge Detection
 10.1.1 Point Detection
 10.1.2 Line Detection
 10.1.3 Edge Detection Using Function edge
 10.2 Line Detection Using the Hough Transform
 10.2.1 Background
 10.2.2 Toolbox Hough Functions
 10.3 Thresholding
 10.3.1 Foundation
 10.3.2 Basic Global Thresholding
 10.3.3 Optimum Global Thresholding Using Otsu's Method
 10.3.4 Using Image Smoothing to Improve Global Thresholding
 10.3.5 Using Edges to Improve Global Thresholding
 10.3.6 Variable Thresholding Based on Local Statistics
 10.3.7 Image Thresholding Using Moving Averages
 10.4 Region-Based Segmentation
 10.4.1 Basic Formulation
 10.4.2 Region Growing
 10.4.3 Region Splitting and Merging
 10.5 Segmentation Using the Watershed Transform
 10.5.1 Watershed Segmentation Using the Distance Transform
 10.5.2 Watershed Segmentation Using Gradients
 10.5.3 Marker-Controlled Watershed Segmentation
 Summary
11 Representation and Description
 Preview
 11.1 Background
 11.1.1 Functions for Extracting Regions and Their Boundaries
 11.1.2 Some Additional MATLAB and Toolbox Functions Used
 in This Chapter
 11.1.3 Some Basic Utility M-Functions
 11.2 Representation
 11.2.1 Chain Codes
 11.2.2 Polygonal Approximations Using Minimum-Perimeter
Polygons
 11.2.3 Signatures
 11.2.4 Boundary Segments
 11.2.5 Skeletons
 11.3 Boundary Descriptors
 11.3.1 Some Simple Descriptors
 11.3.2 Shape Numbers
 11.3.3 Fourier Descriptors
 11.3.4 Statistical Moments
 11.3.5 Corners
 11.4 Regional Descriptors
 11.4.1 Function regionprops
 11.4.2 Texture
 11.4.3 Moment Invariants
 11.5 Using Principal Components for Description
 Summary
 Appendix A M-Function Summary
 Appendix B ICE and MATLAB Graphical User Interfaces
 Appendix C Additional Custom M-functions
 Bibliography
 Index 显示全部信息

已确认勘误

次印刷

页码 勘误内容 提交人 修订印次

Digital image processing using MATLAB
    • 名称
    • 类型
    • 大小

    光盘服务联系方式: 020-38250260    客服QQ:4006604884

    意见反馈

    14:15

    关闭

    云图客服:

    尊敬的用户,您好!您有任何提议或者建议都可以在此提出来,我们会谦虚地接受任何意见。

    或者您是想咨询:

    用户发送的提问,这种方式就需要有位在线客服来回答用户的问题,这种 就属于对话式的,问题是这种提问是否需要用户登录才能提问

    Video Player
    ×
    Audio Player
    ×
    pdf Player
    ×
    Current View

    看过该图书的还喜欢

    some pictures

    解忧杂货店

    东野圭吾 (作者), 李盈春 (译者)

    loading icon