This course provides an introduction to basic concepts, methodologies and algorithms of digital image processing focusing on the following two major problems concerned with digital images: (1) image enhancement and restoration for easier interpretation of images, and (2) image analysis and object recognition. Some advanced image processing techniques (e.g., wavelet and multiresolution processing) will also be studied in this course. The primary goal of this course is to lay a solid foundation for students to study advanced image analysis topics such as computer vision systems, biomedical image analysis, and multimedia processing & retrieval.
For the last few decades, image processing has emerged as an important technology to extract useful information for scene understanding. To develop next-generation image processing systems, it is essential to equip our students with a deep understanding of the challenges in image understanding, and with advanced skills to develop image processing techniques by integrating approaches from information processing and pattern recognition. This course will provide both basic and in-depth coverage of image processing techniques for students to develop information processing systems. In particular, this coruse will help students understand many image processing approaches for scene analysis and understanding; to acquire working knowledge of many image processing systems; to have a hands-on experience on analyzing a variety of images for image understanding.
Percentage of Course
|1. Image processing fundamentals and human vision system||10%|
|2. Digital image enhancement techniques: point processing; spatial filtering||10%|
|3. Digital image enhancement in the frequency domain||10%|
|4. Digital image restoration: inverse filtering; Wiener filtering||15%|
|5. Color image processing||10%|
|6. Digital image compression techniques and standards: source coding; entropy coding, transform and predictive coding; JPEG; MPEG||10%|
|7. Image Segmentation: edge detection; threshoding; region segmentation||20%|
|8. Advanced topics: Morphology and recognition||10%|
|9. Advanced topics: Wavelets and multi-resolution processing||5%|