南京理工大学
《Fundamentals of Image Analysis》课程内容简介
课程编码 S106C004 课程类别 必修课
课程名称 Fundamentals of Image Analysis
英文名称 Fundamentals of Image Analysis
开课院系 计算机科学与工程学院
开课季节 秋学期 授课方式 面授讲课
考核方式 考试 课件地址
考试方式 闭卷 成绩计算方法 期末100%
课程总学时 32 课程学分 2
实验学时 适用对象
课程类型 理论课 课程属性 必修
任 课 教 师
教师姓名性别所属院系职称年龄
肖亮 计算机科学与工程学院 教授 45

教学目标:
This is an advanced senior and graduate level elective course on Digital Image Processing and Analysis, which provides a comprehensive theory of various image processing tasks and the practical experience to simulate them. Upon the completion of this course, the students will have gained a hands-on experience about the below topics through extensive simulation assignments.
? To study the image fundamentals and mathematical transforms necessary for image processing.
? To study the image enhancement techniques
? To study image restoration procedures.
? To study the image compression procedures.
? To study the image segmentation and representation techniques.

课程内容:
In this class, we are going to learn about the basic principles and tools used to process images and videos, and how to apply them in solving practical problems. This course on fundamentals of image analysis is core course for graduate students. The course provide general introduction on the basic principles, collection of algorithms on image processing and analysis. The main contents include: digital image fundamentals, spatial image enhancement technique, basic transformations and frequency domain filters, image restoration and reconstruction.
Chapter 1: Digital Image Fundamentals          2h
  What is an image?
  Image Representation
  Human visual system
  Sampling and Fourier analysis
Chapter 2:Spatial Image enhancement Technique   4h
Basic grey level transformation
Histogram equalization
Image subtraction
Image averaging
Spatial filtering: Smoothing, sharpening filters – Laplacian filters
Chapter 3:Basic transformations and Frequency domain filters  4h
Introduction to Fourier Transform and DFT – Properties of 2D Fourier Transform – FFT – Separable Image Transforms -Walsh – Hadamard – Discrete Cosine Transform, Haar, Slant – Karhunen – Loeve transforms.
  Frequency domain filters : Smoothing – Sharpening filters – Homomorphic filtering
Chapter 4:Image Restoration and Reconstruction  6h
Model of Image Degradation/restoration process
Noise models
Inverse filtering
Least mean square filtering
Constrained least mean square filtering
Blind image restoration
Pseudo inverse
Singular value decomposition
Chapter 5:?Morphological Image Processing  4h
  Erosion, dilation, opening, closing
  Basic Morphological Algortihms: hole filling, connected components, thinning,
skeletons
Chapter 6: Color Image Processing    2h
  Color Models
  Color Transforms
  Image Segmentation Based on color
Chapter 7: Image Compression    4h
  Fundamentals
  Basic Compression Methods
Chapter 8: Image Segmentation and measurements    6h
Edge detection – Thresholding - Region Based segmentation
Boundary representation: chair codes- Polygonal approximation – Boundary segments
boundary descriptors: Simple descriptors-Fourier descriptors - Regional descriptors  
Texture
Requirement for Students:
? Emphasis on understanding
Chapter 1,2,3,4,8
? General on understanding
       Chapter 5,6,7
? Homework (4 times) will designed for Matlab Programming on Image Analysis
? Grading depends on Homework (4 times), 20%, and Final Examination 80%.

适用学生:
全日制硕士    非全日制硕士    留学硕士    进修硕士    硕博连读    本科直博    全日制博士    留学博士    进修博士    在职专硕    其他    

预修课程:
预修课程:
Experience with C/C++ or Matlab.  Courses on Matrix Theory, Probability Theory

参考书目:
Textbooks:
[1] Digital Image Processing (3rd edition), Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, 2007, ISBN 013168728X, http://www.imageprocessingplace.com
[2] Digital Image Processing Using MATLAB, Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins, Prentice-Hall, 2003. ISBN 0130085197

Additional References:
[1] Handbook of Image and Video Processing, Publisher: Academic Press; 2 edition (June 21, 2005), Alan C. Bovik (Author)  
[2] Computer Vision Research Groups:http://www-2.cs.cmu.edu/~cil/v-groups.html
??ITK - Segmentation & Registration Toolkit

备注: