数字图像处理

课程编码：1801010812I0P1005Y 英文名称：digital image processing 课时：40 学分：2.00 课程属性：学科核心课 主讲教师：王伟强

This course is designed for graduate students majoring in computer science, automatic control, and electronic engineering. The course covers classical methods of image processing and analysis, including key concepts, algorithmic ideas, and classical techniques. The main topics covered include image models, spatial and frequency processing techniques, image restoration, color image processing, wavelet analysis, multi-resolution analysis techniques, morphological processing, image coding, edge detection, and shape description. By the end of this course, students will have a solid understanding of the basic concepts and classical algorithms of image processing. This will provide a strong foundation for further study in machine vision and image understanding. Through practical exercises using Matlab, students will be able to apply their knowledge in a flexible and effective manner, improving their hands-on skills and research abilities.

大学基础数学（线性代数，高等数学，概率论）

第一章 Introduction and Matlab tutorial 3.0学时 王伟强
第1节 course introduction
第2节 teaching content and schedule
第3节 the Matlab language
第4节 basic correlation function of image processing-related toolbox
第二章 image spatial processing technology 5.0学时 王伟强
第1节 brightness transformation
第2节 histogram equalization and histogram matching
第3节 analysis and understanding of convolution and correlation calculation, convolution and linear shift-invariant system
第4节 smooth linear filter
第5节 statistical sorting filter
第6节 sharpening filter
第三章 image frequency processing technology 5.0学时 王伟强
第1节 Fourier positive and negative transformation and its origin
第2节 properties of Fourier transform
第3节 the relationship between spatial filtering and frequency filtering
第4节 some problems in engineering implementation
第5节 low-pass smoothing filter
第6节 sharpening smoothing filter
第7节 homomorphic filter
第四章 image restoration 5.0学时 王伟强
第1节 image degradation and recovery process model
第2节 noise model
第3节 construction and implementation of general random noise generator
第4节 estimation of noise parameters
第5节 restoration of spatial filtering in the presence of noise
第6节 frequency-domain filters for periodic noise
第7节 estimation of degenerate functions
第8节 the inverse filtering
第9节 wiener filtering
第10节 constrained least squares filter
第11节 geometric mean filtering
第12节 geometric transformation
第五章 color image processing 4.0学时 王伟强
第1节 what is color
第2节 color expression and measurement experiments
第3节 common color space
第4节 full-color image processing
第六章 wavelet analysis and multi-resolution analysis technology 9.0学时 王伟强
第1节 image pyramids
第2节 perfect reconstruction filter
第3节 haar transformation
第4节 multi-resolution analysis theory
第5节 one-dimensional wavelet transform
第6节 fast wavelet transform
第7节 two-dimensional wavelet transform
第8节 wavelet packet
第七章 image coding 3.0学时 王伟强
第1节 basic principles and concepts of image compression
第2节 source coding and channel coding
第3节 basic knowledge of information theory
第4节 DCT transformation and other image transformation
第八章 morphological processing 3.0学时 王伟强
第1节 Background knowledge
第2节 expansion and corrosion
第3节 open and closed operations
第4节 hit and miss transform
第5节 some basic morphological algorithms
第九章 edge detection and shape description 3.0学时 王伟强
第1节 filter with point and line detection
第2节 Canny edge detection algorithm
第3节 corner detection algorithm
第4节 Hough transform
第5节 watershed segmentation algorithm
第6节 shape representation

Wang Weiqiang is currently a professor and doctoral supervisor at the School of Computer Science and Technology, University of Chinese Academy of Sciences. His main research interests include computer vision, machine learning, and intelligent human-computer interaction. He joined the Institute of Computing Technology, Chinese Academy of Sciences in May 2001 as an assistant researcher and was promoted to associate researcher in October 2001. In August 2003, he joined the School of Information Science and Technology, Graduate University of Chinese Academy of Sciences as an associate professor. From October 2004 to September 2005, he was a visiting scholar at Carnegie Mellon University in the United States. He was appointed as a professor in June 2009. He has undertaken research and development work for key projects such as the 863 Program, the National Science and Technology Support Program sub-project, the National Natural Science Foundation of China, key international cooperation and exchange projects, and key research and development projects. He has published more than 130 research papers in important domestic and international journals and conferences.