George Mason University

Computer Science Department

Course Number: CS686

Course Title: Image Processing and Applications

Instructor: Arun Sood

Office Phone: 993-1524

E-mail: asood@gmu.edu

Office: 451/S&T II

Office Hours: Tuesday 3:30 to 4:20 PM, Thursday 11:00 to 11:50 am

Pre-requisites: CS 583, CS365 or equivalent

Course Content:

Introduction

• Overview of Image Processing algorithms and hardware
• Visual Perception
• Sampling

Math Concepts

• Graph theoretic
• Linear System theory

Image Transforms

• One and two dimensional Fourier transforms
• Hough transform

Image Enhancement

• Clipping and thresholding
• Histogram modification
• Image Smoothing
• Image filtering

Image Restoration

• Degradation Models
• Inverse Filtering

Image Encoding and Compression

• Run Length Encoding
• Transform Compression
• Predictive Techniques

Applications

• Remote Sensing
• Medical Imaging
• Industrial Imaging

Course Text

Gonzalez and Woods, Digital Image Processing, Second Edition, Prentice Hall, 2002

Reference Texts

1. B.Jahne, "Digital Image Processing – Concepts, Alogorithms and Scientific Applications," Springer Verlag, 1997.

2. A. K. Jain, "Fundamentals of Digital Image Processing," Prentice Hall 1989.

3. Lawrence H. Rodrigues, " Building Imaging Applications with Java(tm) Technology: Using AWT Imaging, Java 2D, and Java Advanced Imaging (JAI)"

4. Programming in Java Advanced Imaging
    http://java.sun.com/products/java-media/jai/forDevelopers/jai1_0_1guide-unc/

5. Gonzalez, Woods, Eddins, “Digital Image Processing using Matlab”, Prentice Hall, 2004

Award of IN grade:

The IN grade policy as indicated in the catalog will be strictly adhered to. You must provide the necessary back-up documentation (e.g. medical certificate) for your application to be considered favorably. In all circumstances the written request, with all the back up documentation, must be received before the final exam week.

Grade Computation(tentative)

Project I 10%
Project II: 20%
Project III: 30%
Mid-term Exam: 15%
Final Exam 20%
Class Participation 5%

Projects

Project I introduces the concepts that will be studied in this course, by treating a real-world problem situation.

Project II will involve the computation of 2-D Fourier Transform, and demonstration of some of the properties of the transform.

Project III will be a group project. The project will involve the implementation of image compression/encoding techniques. It will involve the comparative analysis of these approaches, by using a set of noise-free and noisy images.

In all the projects you will be given the minimum requirements, and bonus points will be given for relevant and significant additional work. 

GMU Academic Calendar

Final Exam Schedule

Honor Code