NYU-Poly, Electrical & Computer
EL5123 /BE6223 ---- Image
Processing, Fall 2011
Course Description: This
course introduces basic concepts and techniques in digital image processing:
image acquisition and display using digital devices, properties of human visual
perception, sampling and quantization, sampling rate conversion, contrast
enhancement, two-dimensional Fourier transforms, linear and nonlinear filtering,
morphological operations, noise removal, image deblurring,
edge detection, image registration and geometric transformation, and multiresolution representation using wavelets, and image
compression (including the JPEG and JPEG2000 standard). Students will learn to
implement some image processing algorithms on computers using C-programming or
Prerequisites: EE 3054 (Signals,
Systems, and Transforms), Knowledge of basic matrix operations and probability;
basic programming skill; senior or graduate student status. This course can be
used to form a two-course sequence with EL6122 or EL5823.
Wang, Office: LC256, email: yao
at poly.edu, homepage: http://eeweb.poly.edu/~yao
3:00 - 5:40 PM, Room: RH615
4:30-5:30, Wed. 10:00-11:00, Thur. 10:00-11:00 or by appointment.
Lab room and times: Multimedia Lab
(LC008), check lab open hour at http://eeweb.poly.edu/~yao/EL5143
Text Book: R. C. Gonzalez and R.
E. Woods, Digital Image Processing, Prentice Hall, (3rd Edition) 2008. (If you already have the 2nd ed, you can use it.)
Recommended Readings: A. K. Jain, Fundamentals
of Digital Image Processing, Prentice Hall, 1989 (for more mathematical and
comprehensive treatment than Gonzalez and Woods) (available at Poly Library)
Homework Policy: Weekly written
and/or computer programming assignment, due the following week or as specified.
(Late submission will not be accepted.)
Grading Policy: Exam 1 40%, Exam 2
(non-cumulative) 40%, Homework 20% (Programming assignment 10%, others 10%)
- 9/7: Lecture 1: Overview of
basic image processing techniques and their applications; Image formation
and perception; digital image representation; Matrix algebra review,
Matlab review. Lecture note (updated 9/6/2011) (note: HW
assignment is in lecture note)
- 9/14: Lecture 2: Image
quantization: uniform and nonuniform, visual
quantization (dithering); color coordinate and conversion; color image
quantization. Lecture note (updated
9/20/11) (note: HW assignment is in lecture note)
- 9/21: Lecture 3: Image
contrast enhancement. Lecture
note (updated 9/20/11) (note: HW assignment is in lecture note).
- 9/28: Lecture 4:
Discrete-time Fourier Transforms (DTFT) in 2D; 2 D convolution. Interpretation
of spatial domain filtering in frequency domain. Lecture note (updated 9/28/11) (note: HW
assignment is in lecture note).
- 10/5: Lecture 5: Image smoothing and image sharpening by
spatial domain linear filtering; Edge detection. Lecture note (note: HW assignment is in
- 10/12: Monday class meet. No lecture
- 10/19: Lecture 6: Discrete
Fourier transform (DFT) in 1D and 2D, and image
filtering in the DFT domain. Lecture note.
- 10/26: Lecture 7: Median filtering and
Morphological filtering. Lecture note.
Midterm Review Note (to be updated).
- 11/9: Lecture 8: Image
sampling and sampling rate conversion (resize). Lecture note.
- 11/16: Lecture 9: Lossless
image compression: The concept of entropy and Huffman coding; Runlength coding for bi-level images; CCITT facsimile
compression standards. Lecture
- 11/23: Lecture 10: Lossy image compression: Image quantization revisited;
Predictive coding; Transform coding; JPEG image compression standard. Lecture note.
- 11/30: Lecture 11: Wavelet
transform; JPEG2000 image compression standard. Lecture note
- 12/7: Lecture 12: Imaging
Geometry; Coordinate transformation and geometric warping for image
registration. Lecture note.
- 12/14: Lecture 13: Image
Restoration (denoising and deblurring).
Lecture note. Final review (lecture note)
- 12/21: Final Exam
- Sample midterm exam (F05) with solution,
Sample midterm exam (F08), solution to midterm F08, sample final exam (F04) with solution.
Another sample final exam (F05) (w/o solution),
Final exam F08, Solution to final exam of F08; Final exam F09, Solution to final exam of F09
(please note the correction in the yellow sticker in the pdf file). Midterm exam (F10).
Last updated: 10/25/2011, Yao