This is supplemental course information, designed to give you a fuller picture of the course and an expanded look at the topics covered. This is an unofficial document. The USC Course Catalog is the binding description of all university courses. Information such as books, materials covered, and the order of topics is subject to change. Please consult instructor for this semseter to get more upto date course information.
Catalogue 2006-07:
Image sampling, 2-D image transform, image enhancement, geometric image modification, morphologic processing, edge detection, texture analysis, image filtering and restoration. Graduate standing. Recommended preparation: EE 401, EE 464.
Textbook:
1. William K Pratt: Digital Image Processing, 3rd Edition, John Wiley & Sons Inc., 2001
Course monitors:
C.-C. Jay Kuo
Topics:
1. Image Enhancement and Noise Removal
2. Edge Detection
3. Morphological Processing
4. Digital Halftoning
5. Geometrical Modification
6. Texture Analysis
7. Object Shape Recognition
8. Color Image Processing
9. Image Restoration
10. Image Sampling and Transforms
11. Image Watermarking and Data Hiding
12. Image Indexing and Retrieval
Course Objectives:
1. To provide students with a substantial understanding of a wide range of image processing algorithms with hand-on experience.
2. To offer students different possible real-world applications of digital image processing techniques
3. To expose students to several new research topics such as image data hiding and image indexing, archiving and retrieval
Course Outcomes:
The students will be able to
1. understand the basic principles and algorithms of a wide range of image processing techniques
2. implement various algorithms with suitable programming tools
3. perform independent studies on one selected topic in the digital image processing field
4. know recent technology development trends and new research topics
Projects and Term Paper:
Three programming-based projects will be assigned.
1. Image enhancement and noise removal
2. Edge detection, morphological processing and digital half-toning
3. Geometrical modification, texture classification & segmentation and object shape recognition
The programs can be implemented in either C or Matlab. There is a mid-term exam but not final exam. A term paper is required at the end of the semester.
Prepared by: Jay Kuo Date: 10/1/2006
