University of California, Berkeley
Electrical Engineering and Computer Sciences Department
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EE225B, Spring 2018
Digital Image Processing

Tue. and Thu.: 09:30 - 11:00 am
540 Cory

Prerequisite:   EE120

Required Text:

  1. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 4th Edition.

Video lectures:
EE225B, Spring 2018

Course Details:

Lecturer:
Professor Avideh Zakhor
avz@eecs.berkeley.edu
507 Cory Hall
Phone: (510) 643-6777

Office Hours:
Thursday 11:00am - 12:00pm in 507 Cory

TA:
Xinlei Pan
xinleipan@berkeley.edu

Office Hours:
Monday 4-5 pm, location: Cory 504; Friday 4-5 pm, location: Soda 510 VCL.


Recommended Texts:

  1. Bovik, Handbook of Image and Video Processing, Academic Press 2000.
  2. N. Netravali and Barry G. Haskell, Digital Pictures, Plenum Press, 1988.
  3. W.K.Pratt, Digital Image Processing, John Wiley and Sons, 1992.
  4. A.M. Tekalp, Digital Video Processing, Prentice Hall, 1995.

Other useful references:

  1. D. E. Dudgeon and R. M. Mersereau, Multi-Dimensional Digital Signal Processing, Prentice Hall, 1984.
  2. V. Oppenheim and R. W. Schafer, Digital Signal Processing, Prentice-Hall, 1975.
  3. T. S. Huang, editor, Two-Dimensional Digital Signal Processing, Topics in Applied Physics, vol. 42 and vol. 43, Springer-Verlag, 1981.
  4. S. K. Mitra and M. P. Ekstrom, editors, Two-Dimensional Digital Signal Processing, Dowden, Hutchison, and Ross, 1978.
  5. R. C. Gonzalez and P. Wintz, Digital Image Processing, Addison-Wesley, 1979.
  6. H. C. Andrews and B. R. Hunt, Digital Image Restoration, Prentice-Hall, 1977.
  7. H. C. Andrews, Tutorial and Selected Papers in Digital Image Processing, IEEE Press, 1978.
  8. W. F. Schrieber, Fundamentals of Electronic Imaging Systems, Springer-Verlag, 1986.
  9. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989.

Outline of Topics:

  1. Image sensing and acquisition, sampling, quantization
  2. Spatial transformations, filtering in space domain and frequency domain.
  3. Image restoration, enhancement, reconstruction; computed tomography
  4. Wavelets and multi-resolution processing
  5. Image and video compression and communication; watermarking
  6. Morphological Image processing
  7. Color processing
  8. Edge detection; feature extraction; SIFT, MSER
  9. Image segmentation
  10. Neural networks and deep learning
  11. 3D image processing
  12. Applications to augmented reality and virtual reality

Homework:

Homework will be issued approximately once every one or two weeks. They will either consist of written assignments, Matlab assignments or C programming assignments. Homework will be graded, and will contribute 55% to the final grade. Homework handed in late will not be accepted unless consent is obtained from the teaching staff prior to the due date. There will be a project that will constitute 35% of your grade. The project can be individual or in a group. You are to submit a proposal to the instructor by the end of March. More details on the project will be provided later, and a list of suggested topics will be provided. In addition, 10% of your grade will be for in class participation.


Announcements:

  • Welcome to EE225B!

  • 01/19/18: Instructions on how to get matlab are here.
  • 01/30/18: Extra office hour this week: 02/02/18 Fri 4-5 pm at Cory 504.

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Lecture Notes:

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Textbook Reading Schedule:
  • Week 2(1/22-1/26): Read Chapters 1 and 2 of Gonzalez and Woods


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Literature Reading:

Discussion Notes:

Homework:

Submit files to ee225b2018sp@gmail.com


Handouts:
  • Signals, Systems and Fourier Transform
  • Multi-Dimensional Fourier Transform
  • Image Restoration
  • Embedded Image Coding Using Zerotrees of Wavelets Coefficients
  • Review of Algorithms for Reconstruction of images from Fourier Transform Magnitude

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  •  Last updated 4/28/14 by KCM