Digital Image Processing

Course Content

Digital image processing has become one of the most popular courses in computer science and electrical engineering. The techniques of digital image processing have been rapidly developed and widely adopted in tremendous applications. This course gives a series of introductory lectures on the basic theories and implementations of digital image processing techniques. The major topics cover Digital Image Fundamentals, Image Enhancement, Image Restoration, Color image processing, Segmentation, Wavelets processing, and Morphological image processing. Some newly developed Deep learning techniques for image processing will also be included. The course work includes programming assignments and one examination. It is a fundamental course for digital image processing. Some recent development of artificial intelligence based image processing techniques will also be introduced in these lectures.

Prerequisite

None

Textbook

  • R.C Gonzalez and R.E. Woods, Digital Image Processing, Global 4th ed., Pearson, 2018.
  • M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine Vision, 4th ed., Cengage Learning, USA, 2015.

Reference books

  • RC Gonzales, RE Woods, SL Eddins, Digital Image Processing Using MATLAB, 2nd ed., Tata McGraw Hill Education, 2011.
  • Atam P. Dhawan, Medical Image Analysis, IEEE Press, Wiley-Interscience, 2011.
  • Deep learning for image processing applications [electronic resource] / edited by D. Jude Hemanth and Vania Vieira Estrela, IOS Press, 2017.
  • Pro deep learning with TensorFlow : a mathematical approach to advanced artificial intelligence in Python / by Santanu Pattanayak, Springer eBooks 2017.
  • Practical computer vision applications using deep learning with CNNs: with detailed examples in Python using TensorFlow and Kivy / by Ahmed Fawzy Gad, Springer eBooks, 2018.
  • W.K. Pratt, Digital Image Processing, 4th ed., Wiley inter-science, 2007.

Grading policy

  • One examination (50%)
  • assignment one (15%)
  • assignment two (or final Project) (35%)

New update

  • [2019/10/17] 上課投影片Ch1,2,3己放上moodle
  • [2019/09/18] Page update

Resources

  • Handout and Homework
  • ftp://140.116.247.97 port:102
  • id:imagehw2
  • pw:imagehw2
  • dir:file/

公告

  • 郭振鵬 shinyakuok@gmail.com;

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