CpE 645 Image Processing Instructor: Dr. Hong Man                                                      Office: 201 ECE (Burchard) ○ Phone: (201) 216-5038 ○ Fax: (201) 216-8246 Email: hman@stevens-tech.edu Class Homepage: https://webct.stevens-tech.edu/webct/public/home.pl

Office Hours:    Friday, 2:00 – 6:00 PM

Course Text:     Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Second Edition, Prentice Hall, 2002, ISBN: 0201180758

Course Prerequisite:  Introduction to Digital Signal Processing, or equivalent.

Course Grading:

    Your grade of this course will be determined on the following distribution:

    Homework:           20%
    Mid-term Exam:    20%
    Term Project:        30%
    Final Exam:           30%

Homework:

    Homework will be assigned periodically. All problem sets are expected to be completed according to the instructions, and they are usually due in one week.  Homework will be coarsely graded and returned. Homework solutions will also be provided.

Term Project:

    The intention of the term project is to give you a chance to investigate a specific area of the image processing field that is of interest to you. Topics for the term project will be provided in early February. Each term project is to include a 5-page report which describes the nature of your work, and a 5-10 min. computer demo to show your results.

Class Dates:

09-05, 09-12, 09-19, 09-26, 10-03, 10-10, 10-17(mid-term), 10-24, 10-31, 11-07, 11-14, 11-21, 12-5, 12-12 (project due).

 

Content

1.     Multidimensional Digital Signal Processing
·      2-D signals and systems
·      Frequency representations, DTFT
·      Filters and filtering operation
·      Sampling theory

2.     2-D Transforms
·      DFT, DCT, DST, WHT, KLT

3.     Image Perception and Physical Modeling
·      Human visual system
·      Light, brightness, contrast
·      Color modeling and representation

4.     Image Enhancement
·      Histogram based approaches
·      Linear and morphological filtering based approaches
·      Frequency domain approaches
·      Gradient methods

5.     Image Restoration
·      Degradation and observation models
·      Inverse filtering,  iterative restoration, extrapolation

6.     Image Reconstruction from Projection
·      Projections of 2-D object
·      Radon Transform
·      Convolution and back projection algorithm

7.     Image Analysis
·      Feature detection and extraction
·      Image segmentation

8.     Image Coding
·      Transformation, quantization, entropy coding
·      JPEG coding algorithm
·      Subband coding algorithm, JPEG2000

9.     Video Coding
·      Digital video, spatial-temporal sampling
·      Motion representation and estimation
·      MPEG, etc.

hman@stevens-tech.edu                                                    Last update: September 2, 2003