Digital Image Processing I
Deterministic and stochastic modeling of images, linear and nonlinear filtering, and image transformations for coding and restoration. A variety of web based laboratory experiments based on a combination of Matlab and C programming environments will be used.
ECE63700
Credit Hours:
3Learning Objective:
To cover the basic analytical methods which are widely used in image processing; to cover issues and technologies which are specific to images and image processing systems; to develop experience with using computers to process images.Description:
Deterministic and stochastic modeling of images, linear and nonlinear filtering, and image transformations for coding and restoration. A variety of web based laboratory experiments based on a combination of Matlab and C programming environments will be used.
Topics Covered:
1. Continuous Parameter Signals and Systems 2. Discrete Parameter Signals and Systems 3. Image topology and segmentation 4. Imaging Perception and Representation 5. Resolution conversion 6. Image Enhancement and Filtering (Lab) 7. Image Quantization and Halftoning 8. Image Coding (Lab) 9. Image ReconstructionPrerequisites:
Well prepared students should have a background in at least two out of the three following topics: linear time-invariant systems theory including the Fourier transform; random variables and random processes; and computer programming in the C programming language. Most background material is covered in the course, but at a rapid pace.Web Address:
https://engineering.purdue.edu/~bouman/ece637
Homework:
8 laboratory assignments will be assigned during the semester with the average laboratory requiring approximately 8 hours to complete.Projects:
None.Exams:
Two exams and one final exam.Textbooks:
Required:
"Handbook of Image and Video Processing (Communications, Networking and Multimedia) Alan C. Bovik Academic Press 9780121197902 1st Edition "