EE225B, Spring 2011
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, second edition, 2002.
Webcast:
EE225B, Spring 2007
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 pm, 507 Cory Hall
Grader:
Aaron Hallquist
aaron.hallquist@gmail.com
Course Assistant:
Lea Barker
(510) 642-2384
leab@eecs.berkeley.edu
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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.
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 February. 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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4/29/11: The Powerpoint for Lecture 26 has now been uploaded.
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4/6/11: An additional reading for the April 12th class discussion has now been posted here.
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2/28/11: The SP11 EE225B project proposal date has been changed to Tuesday, March 8.
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2/22/11: The SP11 EE225B projects are now posted under Course Handouts.
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2/22/11: The slides for the Feb. 22nd class discussion are now posted below.
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2/7/11: The slides for the Feb. 8th class discussion are now posted below.
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Welcome to EE225B!
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- Lecture 1: What is Image Processing? and Systems
Tues., Jan. 18, 2011
- Lecture 2: Fourier Transform and Fourier Transform Properties
Thurs., Jan. 20, 2011
- Lecture 3: Tomography
Tues., Jan. 25, 2011
- Lecture 4: Reconstruction from Fourier Transform Magnitude
Thurs., Jan. 27, 2011
- Lecture 5: Reconstruction from Fourier Transform Phase and
Signal Reconstruction from Level Crossing
Tues., Feb. 1, 2011
- Lecture 6: 2D Z Transform
Thurs., Feb. 3, 2011
- Lecture 7:
Anat Levin, Rob Fergus, Fredo Durand, William T. Freeman:
Image and Depth from a Conventional Camera with a Coded Aperture
Slides by Fu Chung and Jiamin Bai.
Tues., Feb. 8, 2011
- Lecture 8: Image-based Localization for Augmented Reality Applications
Jerry Zhang, Aaron Hallquist, and Avideh Zakhor:
Location-based Image Retrieval for Urban Environments
Thurs., Feb. 10, 2011
- Lecture 9: Image Enhancement: Intensity Transformation Function and
Histogram Equalization and Matching
Tues., Feb. 15, 2011
- Lecture 10: CANCELLED due to BEARS Conference
Thurs., Feb. 17, 2011
- Lecture 11: Distinctive Image Features from Scale-Invariant Keypoints (Powerpoint)
David G. Lowe: Distinctive Image Features from Scale-Invariant Keypoints (Reading)
Tues., Feb. 22, 2011
- Lecture 12: Image Enhancement Through Spatial Filtering; Edge Detection
Thurs., Feb. 24, 2011
- Lecture 13: Efficient Visual Search (Powerpoint)
Josef Sivic and Andrew Zisserman Efficient visual search for objects in video (Reading)
Tues., Mar. 1, 2011
- Lecture 14: Restoration: Noise Removal in the Space Domain
Thurs., Mar. 3, 2011
- Lecture 15: Normalized Cuts and Image Segmentation (Powerpoint)
Jianbo Shi and Jitendra Malik Normalized cuts and image segmentation (Reading)
Tues., Mar. 8, 2011
- Lecture 16: Restoration: Weiner Filtering
Thurs., Mar. 10, 2011
- Lecture 17: Restoration: Adaptive Weiner Filtering; Constrained Least Squares, Iterative Restoration.
Blind Deconvolution; Homomorphic Processing
Tues., Mar. 15, 2011
- Lecture 18: SensEye: A Multitier Camera Sensor Network (Powerpoint) PDF of Powerpoint
Purushottam Kulkarni, Deepak Ganesan, Prashant Shenoy and Qifeng Lu:
SensEye: A Multitier Camera Sensor Network (Reading)
Thurs., Mar. 17, 2011
- Lecture 19: Sparse MRI: The Application of Compressed Sensing for Rapid MRI (Powerpoint)
Michael Lustig, David Donoho, and John M. Pauly Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging (Reading)
Tues., Mar. 29, 2011
- Lecture 20: Objectives of Image Coding.
Methods of Bit Assignment
Thurs., Mar. 31, 2011
- Lecture 21: Transform Image Coding
Tues., Apr. 05, 2011
- Lecture 22: Subband, Pyramid and Wavelet Coding and Subband Coding and JPEG-2000 Compression
Thurs., Apr. 07, 2011
- Lecture 23: Image Stitching (Powerpoint)
Matthew Brown and David G. Lowe:
Automatic Panoramic Image Stitching using Invariant Features (Reading)
Class panorama: Left Right Panorama
Tues., Apr. 12, 2011
- Lecture 24: Fourier transform, Short Term Fourier Transform, and Wavelets and Multi-Resolution Expansion
Thurs., Apr. 14, 2011
- Lecture 25: Embedded Zerotree Wavelet
Tues., Apr. 19, 2011
- Lecture 26: Recent Advances in Augmented Reality (Powerpoint) (PDF version)
Ronald Azuma, Yohan Baillot, Reinhold Behringer, Steven Feiner, Simon Julier, Blair MacIntyre:
Recent Advances in
Augmented Reality (Reading)
Thurs., Apr. 21, 2011
- Lecture 27: Motion Estimation and Video Standards and Fractal Compression and Vector Quantization
Tues., Apr. 26, 2011
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- Reading 1 To be discussed on Feb. 8th in class.
Anat Levin, Rob Fergus, Fredo Durand, William T. Freeman:
Image and Depth from a Conventional Camera with a Coded Aperture
Slides by Fu Chung and Jiamin Bai.
- Reading 2:
To be discussed in class on Feb. 15th
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Reading 3: David G. Lowe: Distinctive Image Features from Scale-Invariant Keypoints
In class discussion: Feb. 22nd.
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Reading 4: Josef Sivic and Andrew Zisserman Efficient visual search for objects in video
In class discussion: March 1st
- Reading 5: Jianbo Shi and Jitendra Malik Normalized cuts and image segmentation
In class discussion: March 8th
- Reading 6: Purushottam Kulkarni, Deepak Ganesan, Prashant Shenoy and Qifeng Lu:
SensEye: A Multitier Camera Sensor Network
In class discussion: March 17th
- There is no class on March 22nd (Spring Break)
- Reading 7: Michael Lustig, David Donoho, and John M. Pauly
Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging
In class discussion: March 29th
- Reading 8: Ronald Azuma, Yohan Baillot, Reinhold Behringer, Steven Feiner, Simon Julier, Blair MacIntyre:
Recent Advances in
Augmented Reality
In class discussion: April 5th
- Reading 9: Richard Szeliski Image Alignment and Stitching: A Tutorial
*NEW* Matthew Brown and David G. Lowe:
Automatic Panoramic Image Stitching using Invariant Features
In class discussion: April 12th
- Reading 10: Martin A. Fischler and Robert C. Bolles:
Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
In class discussion: April 17th
Submit files to
aaron.hallquist@gmail.com
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Homework 1 - Lab: Tomography -
Pyramid.bmp
Due in class Thurs. Feb. 3rd, 2011
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Homework 2 - Lab: Phase-only image reconstruction -
Phase.dat, Magnitude.dat,
Test.bmp
Due in class Thurs. Feb. 10th, 2011
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Homework 3 -
Problems 1.28, 1.30, 1.33, 1.34 and 1.35 from J. Lim's book.
Due in class Thurs. Feb. 17th, 2011
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Homework 4 - Lab: Image Enhancement -
Berkeley.jpg
Due in class Thurs. March 3, 2011
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Homework 5 - Lab: Image Restoration -
NoisyImg.bmp, NoisyBlur.bmp
Due in class Tues. Mar. 29, 2011
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Homework 6 - Lab: Image Compression -
Compressed Lab Figures, IGS.pdf
Due in class Tues. Apr. 12, 2011
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Homework 7 - Lab: Wavelet Transforms and Coding -
Compressed Lab Figures
Due in class Thurs. Apr. 21, 2011
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Objectives of Image Coding and Iterative Procedures
(Note: These files are in progress.)
(This is a very large file, download before opening.)
- Additional Class Materials
- "Basic Methods for Image Restoration and Identification," Reginald L. Lagendijk and Jan Biemond
- Proposed Projects for EE225B
Proposals are due in class on Tuesday, Mar. 8, 2011.
Presentation of projects, Thursday, May 5, 2011, in class.
- Art Files
Chapter 1 - Introduction
Chapter 2 - Digital Image Segmentation
Chapter 3 - Image Enhancement in the Spatial Domain
Chapter 4 - Image Enhancement in the Frequency Domain
Chapter 5 - Image Restoration
Chapter 8 - Image Compression
Chapter 10 - Image Segmentation
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"A Theory for Multiresolution Signal Decomposition: The Wavelet Representation," Stephane G. Mallat
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Wavelets, Approximation, and Compression, by Martin Vetterli, 2001
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Wavelets and Signal Processing, by Oliver Rioul and Martin Vetterli, 1991
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