Image Processing and Data Visualization
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
2021-01-26