**NYU-Poly,
Electrical & Computer Engineering**

**EL5123 /BE6223 ---- Image Processing, Fall 2013**

http://eeweb.poly.edu/~yao/EL5123

**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
MATLAB.

**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.

**Course Instructor:**

**Yao Wang, Office: 2MTC 9.107, email:
yao at poly.edu**, **tel****: 718-260-3469**, **homepage: http://eeweb.poly.edu/~yao**

**Teaching Assistant:**** **

**Fanyi**** Duanmu,
email: dmfynyu@gmail.com**

**Lecture:**

**Mon. 10:20 AM – 12:50 PM, 2 MTC 9.011**

**Office Hour:**

**2MTC 9.007, Mon. 4:30-5:30, Wed.
4:30-5:30, or by appointment.**** **

**Text Book:** R. C. Gonzalez and R.
E. Woods, Digital Image Processing, Prentice Hall, (3rd Edition) 2008. ISBN
number 9780131687288. (If you already have the 2^{nd} ed, you can use it.)

**Recommended **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%)

**Course Schedule**

- 9/9: 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)
- 9/16: 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)
- 9/23: Lecture 3: Image contrast enhancement. Lecture note (updated
9/20/11) (note: HW assignment is in lecture note).
- 9/30: 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).
- 10/7: Lecture 5: Image smoothing and image
sharpening by spatial domain linear filtering; Edge detection. Lecture note (updated 10/19/12).
- 10/14: Fall break, no class:
- 10/16 (Wed: Monday class meet): Lecture 6: Discrete
Fourier transform (DFT) in 1D and 2D, image filtering in the DFT domain. Lecture note.
- 10/21:
*10/28:**Midterm Exam*. Midterm Review Note (updated 10/21/13).- 11/4: Lecture 8: Image sampling and sampling rate
conversion (resize). Lecture note.
- 11/11: Lecture 9: Lossless image compression: The
concept of entropy and Huffman coding; Runlength
coding for bi-level images; CCITT facsimile
compression standards. Lecture
note.
- 11/13: Withdraw deadline
- 11/18: Lecture 10: Lossy
image compression: Image quantization revisited; Predictive coding;
Transform coding; JPEG image compression standard. Lecture note. (updated 11/20/12)
- 11/25:
Lecture 11: Wavelet transform;
JPEG2000 image compression standard. Lecture
note
- 12/2: Lecture 12: Imaging Geometry; Coordinate transformation
and geometric warping for image registration. Lecture note. (updated 12/12/12)
- 12/9: Lecture 13: Image Restoration (denoising and deblurring). Lecture note. (updated 12/12/12)
Final review (lecture note)
(updated 12/12/12)
*12/16: Final Exam**Sample midterm exam (F05) with solution (updated 10/18/12), 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). Midterm exam F11 (uploaded 10/19/12), solution to Midterm exam F11 (uploaded 10/19/12). Solution to Midterm exam F12 (uploaded 11/14/2012. Final exam F11. Final exam F12. Solution to F12 Final Exam. Midterm exam F13. Solution to F13 midterm exam. Final exam F13. Solution to F13 final exam*

Last updated: 9/3/2013, Yao Wang