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數字圖像處理概論 版權信息
- ISBN：9787562439677
- 條形碼：9787562439677 ; 978-7-5624-3967-7
- 裝幀：一般膠版紙
- 冊數：暫無
- 重量：暫無
- 所屬分類：>>>
數字圖像處理概論 本書特色
數字圖像處理是信息技術中的一門新興學科，它所涵蓋的內容極其豐富。麥克安德魯編著的《數字圖像處理概論》涵蓋了低層次圖像處理（圖像增強、圖像恢復）和高層次圖像處理（形態學、圖像分割、圖像表示與描述和圖像壓縮）的全部基礎內容，全書可作為圖像處理專業課程本科生雙語教學教材。
數字圖像處理概論 內容簡介
本書是美國Alasdair McAndrew所著Introduction to Digital Image Processing with MATLAB一書的縮編版。按照我國60學時的教學要求縮編而成。
縮編后的內容充實，涵蓋了低層次圖像處理（圖像增強、圖像恢復）和高層次圖像處理（形態學、圖像分割、圖像表示與描述和圖像壓縮）的全部基礎內容，習題和教材內容結合緊密，便于學生鞏固所學知識。同時，縮編作者對原書部分難點進行了注釋，幫助讀者更好地理解所學內容。
本書可作為圖像處理專業課程本科生雙語教學教材。
數字圖像處理概論 目錄
PREFACE
CHAPTER 1 Introduction
1.1 hnages and Pictures
1.2 What is Image Processing?
1.3 Image Acquisition and Samplin~
1.4 Images and Digital Images
1.5 Some Applications
1.6 Aspects of Image Processing
1.7 An hnage-Processing Task
1.8 Types of Digital Images
1.9 Image File Sizes
1.10 Image Perception
Exercises
CHAPTER 2 Images and MATLAB
2.1 Grayscale Images
2.2 RGB Images
2.3 Indexed Color Images
2.4 Data Types and Conversions
2.5 Image Files and Formats
2.6 Files in MATLAB
Exercises
CHAPTER 3 Image Display
3.1 Introduction
3.2 Basics of Image Display
3.3 The imshow Function
3.4 Bit Planes
3.5 Spatial Resolution
3.6 Quantization mad Dithering
Exercises
CHAPTER 4 Point Processing
4.1 Introduction
4.2 Arithmetic Operations
4.3 Histograms
4.4 Lookup Tables
Exerciser
CHAPTER 5 Neighborhood Processing
5.1 Introduction
5.2 Notation
5.3 Filtering in MATLAB
5.4 Frequencies : Low-and High Pass Filters
5.5 Gaussian Filters
5.6 Edge Sharpening
5.7 Nonlinear Filters
Exercises
CHAPTER 6 Image Geometry
6.1 Interpolation of Data
6.2 hnage Interpolation
6.3 General Interpolation
6.4 Enlargement by Spatial Filtering
6.5 Scaling Smaller
6.6 Rotation
Exercises
CHAPTER 7 The Fourier Transform
7.1 Introduction
7.2 The Two-Dimensional DFF
7.3 Fourier Transforms in MATLAB
7.4 Fourier Transforms of Images
7.5 Filtering in the Frequency Domain
7.6 Homomorphic Filtering
Exercises
CHAPTER 8 Image Restoration
8.1 Introduction
8.2 Noise
8.3 Cleaning Salt and Pepper Noise
8.4 Cleaning Gaussian Noise
8.5 Removal of Periodic Noise
8.6 Inverse Filtering
8.7 Wiener Filtering
Exercises
CHAPTER 9 Image Segmentation
9.1 Introduction
9.2 Thresholding
9.3 Applications of Thresholding
9.4 Choosing an Appropriate Threshold Value
9.5 Adaptive Thresholding
9.6 Edge Detection
9.7 Derivatives and Edges
9.8 Second Derivatives
9.9 The Canny Edge Detector
……
CHAPTER 10 Mathematical Morphology
CHAPTER 11 Image Topology
CHAPTER 12 Shapes and Boundaries
CHAPTER 13 Color Procassing
CHAPTER 14 Image Coding and Compressdion
BIBLIOGRAPHY
TERMIOLOGIES USED IN THE BOOK
CHAPTER 1 Introduction
1.1 hnages and Pictures
1.2 What is Image Processing?
1.3 Image Acquisition and Samplin~
1.4 Images and Digital Images
1.5 Some Applications
1.6 Aspects of Image Processing
1.7 An hnage-Processing Task
1.8 Types of Digital Images
1.9 Image File Sizes
1.10 Image Perception
Exercises
CHAPTER 2 Images and MATLAB
2.1 Grayscale Images
2.2 RGB Images
2.3 Indexed Color Images
2.4 Data Types and Conversions
2.5 Image Files and Formats
2.6 Files in MATLAB
Exercises
CHAPTER 3 Image Display
3.1 Introduction
3.2 Basics of Image Display
3.3 The imshow Function
3.4 Bit Planes
3.5 Spatial Resolution
3.6 Quantization mad Dithering
Exercises
CHAPTER 4 Point Processing
4.1 Introduction
4.2 Arithmetic Operations
4.3 Histograms
4.4 Lookup Tables
Exerciser
CHAPTER 5 Neighborhood Processing
5.1 Introduction
5.2 Notation
5.3 Filtering in MATLAB
5.4 Frequencies : Low-and High Pass Filters
5.5 Gaussian Filters
5.6 Edge Sharpening
5.7 Nonlinear Filters
Exercises
CHAPTER 6 Image Geometry
6.1 Interpolation of Data
6.2 hnage Interpolation
6.3 General Interpolation
6.4 Enlargement by Spatial Filtering
6.5 Scaling Smaller
6.6 Rotation
Exercises
CHAPTER 7 The Fourier Transform
7.1 Introduction
7.2 The Two-Dimensional DFF
7.3 Fourier Transforms in MATLAB
7.4 Fourier Transforms of Images
7.5 Filtering in the Frequency Domain
7.6 Homomorphic Filtering
Exercises
CHAPTER 8 Image Restoration
8.1 Introduction
8.2 Noise
8.3 Cleaning Salt and Pepper Noise
8.4 Cleaning Gaussian Noise
8.5 Removal of Periodic Noise
8.6 Inverse Filtering
8.7 Wiener Filtering
Exercises
CHAPTER 9 Image Segmentation
9.1 Introduction
9.2 Thresholding
9.3 Applications of Thresholding
9.4 Choosing an Appropriate Threshold Value
9.5 Adaptive Thresholding
9.6 Edge Detection
9.7 Derivatives and Edges
9.8 Second Derivatives
9.9 The Canny Edge Detector
……
CHAPTER 10 Mathematical Morphology
CHAPTER 11 Image Topology
CHAPTER 12 Shapes and Boundaries
CHAPTER 13 Color Procassing
CHAPTER 14 Image Coding and Compressdion
BIBLIOGRAPHY
TERMIOLOGIES USED IN THE BOOK
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