Image Processing and Data Visualization

Instructor

Yun Chen

Credits

3

Hours

Class: 4:30 pm -5:45 pm (Monday and Wednesday)

Office Hour: TBD

Textbook

Digital Image Processing 4th Edition (Gonzalez and Woods)

Pre-requisite

Matlab programming

Purpose of the course

Introduction to:

•   Matrix operation of image processing.

•   Filter development and information extract for high-content analysis.

•   Pattern recognition and deep learning.

•   Visualization of image data with multi-parameter manipulation.

Grading

Homework: 4 small projects (20% each for the first three, 10% for the fourth)

Final Project (30 %)

Outline

Part 2:

(1) Dynamic image processing: image registration and object tracking.

(2) Correlative analysis in time-series images (4D datasets) and/or hyperspectral images.

Part 3:

(1) Pattern Recognition(2) Deep learning-based image analysis

Part 4:

(1) Visualization of >3D image datasets.

(2) Pipelines of visualizing high-content image datasets (VTK toolkit).

(3) Interactive display with VR.

The Attendance Rule

•   3 pts deduction each AWOL

•   Auditing students < 4 times of absence