Office hours (need appointment)
: Wednesday 3:30pm -- 5:30pm (ED209); Friday 1:30pm -- 3:20pm (ED209)
This course introduces the student to the fundamentals of digital image processing. It covers principles and algorithms used in various image processing applications. Topics include image representation, human visual system, image filtering, restoration, enhancement, segmentation and compression. The course is featured with a series of computer exercises that provide practical experiences on processing digital images using C language and MATLAB. (The lectures are in English.)
- The Final DIP scores are attached here. (Scores) Please let me know before midnight, January 26 (Monday), 2015, if you have any question. No change on scores after that date. 期末成績如附檔，如有任何問題請在1/26/2015午夜前和我聯絡。逾期不修改成績。
By Prof. Sheng-Jyh Wang (王聖智教授) with slight modifications
R.C. Gonzalez and R.E. Woods, Digital Image Processing, 3rd edition, Pearson Education, 2008.
(1) A.N. Netravali and B.G. Haskell, Digital Pictures, 2nd Ed., Plenum Press, 1995.
(2) R.C. Gonzalez, R.E. Woods, and S.L. Eddins, Digital Image Processing Using Matlab, 2nd Ed., McGraw Hill, 2009.
(3) A. Bovik, The Essential Guide to Image Processing, Academic Press, 2009.
(4) R. Szeliski, Computer Vision, Springer-Verlag, 2011
Homework: 50% (~ 4 computer assignments)
Final project: 25%
Examine: 25% (2 hours, open book)
Calculus, Linear algebra, Probability, Signals & Systems, and DSP; programming in C/C++ and Matlab