Course Description:
Image is an essential form of information representation and communication in modern society. Nowadays, billions of images are generated daily in various applications ranging from photography, entertainment, education, and defense to medicine. Digital image processing provides fundamental modeling and computing solutions for image capture, filtering, segmentation, quantization, resampling, super-resolution, and compression solutions.
In this introductory course on digital image processing, we cover the basics in both theory and practice of image sampling, quantization, filtering, and deep convolution, and their applications in segmentation, super-resolution, classification, and compression.
Upon completion of the course, students should be able to understand the current state of the art in the image processing area, have practical programming and system skills to address these problems, and have the basis for future research exploration and industry careers in this area.
Prerequisites:
Probability and Random Process, Signal and Systems, Digital Signal Processing
Instructor:
Assistant Professor Hao Chen, Room 233, Email: chenhao1210@nju.edu.cn. Homepage
Teaching Assistants:
Zhipeng Wang, aloha2020@qq.com, Room 311, 电子楼
Course Schedule:
Tues. 9-11, 仙 II 304
Office Hours:
Every Tuesday before and after class (or by appointment)
Text Book/References:
R. C. Gonzalez, R. E. Woods, Digital Image Processing, 4th Ed.
Grade Policy:
Midterm: 40%, Final: 60%
Syllabus and Course Material:
Week #1 绪论 Introduction [pdf]
Week #2 数字图像基础 - 灰度变换 Digital Image Fundamentals - Intensity Transformations [pdf, pdf, pdf]
Week #3 空间滤波 - 频率滤波（I） Spatial Filtering - Filtering in the Frequency Domain (1) [pdf, pdf]
Week #4 空间滤波 - 频率滤波（II）Filtering in the Frequency Domain (2) [pdf]
Week #5 图像复原与重建 Image Restoration and Reconstruction [pdf]
Week #6 小波变换和其他图像变换 Wavelet and Other Image Transforms [pdf]
Week #7 图像压缩和水印 Image Compression and Watermarking [pdf]
Week #8 形态学图像处理 Morphological Image Processing [pdf]