Digital Image Processing

Description

This course emphasizes general principles of image processing, rather than specific applications. It covers topics such as image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, wavelets, noise reduction and restoration, feature extraction and recognition tasks, and image registration.

Program

Artificial Intelligence 132 CRs

Objectives

• - Understand image processing, computer imaging systems, resolution concerns, and image formats
  - Illustrate image digitization, image properties, and noise in images.
  - Realize image pre-processing enhancements: pixel brightness transformation, geometric transformations, and local filtering using masks.
  - Apply image segmentation: threshold based, edge-based, region based, and matching.
  - Understand shape representation and description.
  - Apply mathematical morphology.
  - Introduce classification and recognition in image analysis.
  - Implement a computer program on Matlab or Python to for an image analysis application.
  - Present a framework for an image analysis application pipeline.