EE225B, Spring 2014
Digital Image Processing
Tue. and Thu.: 11:00 - 12:30 pm
521 Cory
Prerequisite: EE120
Required Text:
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R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, Third edition, 2008.
Video lectures:
EE225B, Spring 2006
Course Details:
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Lecturer:
Professor Avideh Zakhor
avz@eecs.berkeley.edu
507 Cory Hall
Phone: (510) 643-6777
Office Hours:
Thursday 12:30 - 1:30 in 507 Cory
TA:
Rick Garcia
rrgarcia@berkeley.edu
Office Hours:
Wednesday, 4-5 pm, Cory 504
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Course handouts:
Handouts not picked up during lectures can be found with the course assistant.
Recommended Texts:
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J. S. Lim, Two-Dimensional Signal and Image Processing, Prentice Hall, 1990.
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Bovik, Handbook of Image and Video Processing, Academic Press 2000.
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N. Netravali and Barry G. Haskell, Digital Pictures, Plenum Press, 1988.
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W. K. Pratt, Digital Image Processing, John Wiley and Sons, 1992.
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M. Tekalp, Digital Video Processing, Prentice Hall, 1995.
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Richard Szeliski,Computer Vision: Algorithms and Applications, 2010.
Other useful references:
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D. E. Dudgeon and R. M. Mersereau, Multi-Dimensional Digital Signal Processing, Prentice Hall, 1984.
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V. Oppenheim and R. W. Schafer, Digital Signal Processing, Prentice-Hall, 1975.
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T. S. Huang, editor, Two-Dimensional Digital Signal Processing, Topics in Applied Physics, vol. 42 and vol. 43, Springer-Verlag, 1981.
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S. K. Mitra and M. P. Ekstrom, editors, Two-Dimensional Digital Signal Processing, Dowden, Hutchison, and Ross, 1978.
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R. C. Gonzalez and P. Wintz, Digital Image Processing, Addison-Wesley, 1979.
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H. C. Andrews and B. R. Hunt, Digital Image Restoration, Prentice-Hall, 1977.
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H. C. Andrews, Tutorial and Selected Papers in Digital Image Processing, IEEE Press, 1978.
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W. F. Schrieber, Fundamentals of Electronic Imaging Systems, Springer-Verlag, 1986.
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K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989.
Outline of Topics:
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Image reconstruction from partial information
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Two-dimensional (2-D) Fourier transform and z-transform;
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2-D DFT and FFT, FIR and IIR filter design and implementation.
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Basics of Image Processing techniques and perception;
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Image and video enhancement
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Image and video restoration
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Reconstruction from multiple images
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Image and video analysis: Image Representation and models; image and video classfication and segmentation; edge and boundary detection in images
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Image compression and coding
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Video compression
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Image and Video Communication, storage and retreival
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Image and video rendering and assessment
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Image and video Acquisition
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Applications of image processing: Synthetic Aperture Radar, computed tomography, cardiac image processing, finger print classfication, human face recognition.
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 45% 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 45% 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 September. 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 presentation of a research paper assigned by the instructor.
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- Lecture 1: What is Image Processing? and Systems
Tues., Jan. 21, 2014
- Lecture 2: Fourier Transform and Fourier Transform Properties
Thurs., Jan. 23, 2014
- Lecture 3 & 4: Imaging Modalities
Tues., Jan. 28, 2014
Thurs., Jan. 30, 2014
- Lecture 5 : Fundamentals of Image Processing
Tues., Feb. 4, 2014
- Lecture 6: Image Enhancement
Thurs., Feb. 6, 2014
- Lecture 7 : SIFT - Achal, Jerry, and Vaishal's presentation
Tues., Feb. 11, 2014
- Lecture 8 : Image Enhancement
Thurs., Feb. 13, 2014
- Lecture 9 : Binary Features - Patricia and David's presentation
Tues., Feb. 18, 2014
- Lecture 10 : Filtering in the Frequency Domain
Thurs., Feb. 20, 2014
- Lecture 11: Color Image Processing
Tues., Feb. 25, 2014
- Lecture 12: Morphological Image Processing (Part 1)
Thurs., Feb. 27, 2014
- Lecture 13: Image Search - Gautam and Jordan's presentation
Tues., Mar. 4, 2014
- Lecture 14: Image Restoration
Thurs., Mar. 6, 2014
- Lecture 15: Visual Odometry - Cayut and Chaoran's presentation
Tues., Mar. 11, 2014
- Lecture 16: Image Restoration
Thurs., Mar. 13, 2014
- Lecture 17: Augmented Reality
Tues., Mar. 18, 2014
- Lecture 18: Tomography
Thurs., Mar. 20, 2014
- Lecture 19: Image Stitching - Jesus and Hong's presentation
Image Reconstruction from Projections
Tues., Apr. 1, 2014
- Lecture 20: Objectives of Image Coding
Methods of Bit Assignment
Thurs., Apr. 3, 2014
- Lecture 21: Transform Image Coding Waveform Coding
Tues., Apr. 8, 2014
- Lecture 22: Morphological Image Processing (Part 2) MRI Signal Processing and Compressive Sensing - Wenwen Compressive Sensing - Yubei
Thurs., Apr. 10, 2014
- Lecture 23: Examples of Transform Coding JPEG and JPEG2000
Tues., Apr. 15, 2014
- Lecture 24: Pyramid and Subband Coding Computational Photography - Veda
Thurs., Apr. 17, 2014
- Lecture 25: Short Term Fourier Transforms and Wavelets
Wavelet Transform
Tues., Apr. 22, 2014
- Lecture 26: Graphics - Craig
Multi-resolution Expansion Mathematical Treatment of Subband Coding
Thurs., Apr. 24, 2014
- Lecture 27: Reconstruction of Images from Fourier Transform Magnitude or Phase Embedded Zerotree Coding
Tues., Apr. 29, 2014
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- Week 2(1/28-1/30): Read Chapters 1 and 2 of Gonzalez and Woods
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- Topic 1: SIFT - Achal, Jerry, and Vaishal's presentation (Feb. 11) is HERE
David G. Lowe: Distinctive Image Features from Scale-Invariant Keypoints
- Topic 2: Image Search - Gautam Gunjala and Jordan Zhang's presentation (March 4) is HERE
Marius Muja and David G. Lowe, "Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration," International Conference on Computer Vision Theory and Applications (VISAPP), Lisbon, Portugal (Feb 2009).
- Topic 3: Binary Features - Patricia and David's presentation (Feb. 18) is HERE
Marius Muja, David G. Lowe: "Fast Matching of Binary Features". Conference on Computer and Robot Vision (CVPR 2012)
- Topic 4: Stitching - Jesus and Hong (April 1) is HERE
Richard Szeliski: Image Alignment and Stitching: A Tutorial
Matthew Brown and David G. Lowe: Automatic Panoramic Image Stitching using Invariant Features
- Topic 5: Augmented Reality - Lingqi and Yuansi (March 18)
Wagner, Reitmayr, Mulloni: Real Time Detection and Tracking for Augmented Reality on Mobile Phones
- Topic 6: Visual Odometry - Cayut and Chaoran's presentation (Mar. 11) is HERE
Nister, D., Naroditsky, O., Bergen, J., “Visual Odometry for Ground Vehicle Applications”, Journal of Field Robotics, 2006.
- Topic 7: Compressive Sensing - Rohan and Vamsi (paper by R. Baranuik) / Wenwen and Yubei (paper on MRI) (April 8) is HERE and HERE
R. Baranuik:
“Compressive Sensing” Signal Processing Magazine, July 2007
Michael Lustig, David Donoho, and John M. Pauly: Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging
- Topic 8: Computational Photography - Veda (April 15)
Levin, Fergus, Durand, and Freeman: Image and Depth from a Conventional Camera with a Coded Aperturee
- Topic 9: Graphics - Craig's (April 22) presentation is HERE
Paul Debevec: “Image Based Lighting”, Siggraph tutorial, 2005
Submit files to
rrgarcia@berkeley.edu
Additional Class Materials
Multi-Dimensional Fourier Transform
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