CS-345-545 Image Processing

Mathematics, Statistics & Computer Science Department

COURSE NO./TITLE: CS-345/545 (354-545) IMAGE PROCESSING

CREDIT: 3

COURSE DESCRIPTION: Theory and applications of digital image processing. Mathematical foundations and algorithms for enhancement, restoration, compression, segmentation and reconstruction from projections.

Prerequisites: MATH-255 and MATH-275 and CS-341 and STAT-332, or consent of instructor.

TEXTBOOK:

  • Digital Image Processing, 3rd Ed., by Gonzales
  • (Previously used Graphical Kernel System for Turbo Pascal by Mikkelson)

COURSE OBJECTIVES: As a result of taking this course the student shall:

  1. Understand the mathematical basis for image processing methods.
  2. Be able to implement image enhancement, compression, restoration and segmentation algorithms.
  3. Be able to select and apply appropriate image processing techniques in one or more application areas. Graduate students shall in addition be able to:
  4. Acquire a broad understanding of the theoretical basis of image processing.

COURSE OUTLINE:

  1. Digitization and Sampling Methods
  2. Image Enhancement
    -Gray Scale Modification
    -Sharpening
    -Smoothing
  3. Image Compression
    -Error-Free Compression Methods
    -Block Truncation Compression
    -Predictive Compression
  4. Restoration
    -One-Dimensional and Two-Dimensional Fourier Transformation
    -Restoration in the Frequency Domain
    -Geometric Transformations
  5. Segmentation
    -Pixel Classification
    -Edge Detection
    -Thresholding
    -Use of Motion in Segmentation
  6. Reconstruction from Projections and Computed Tomography
  7. Applications

Revised 6/08