| Tuesday |
Thursday |
| . |
Jan. 14 - Introduction
- Introduction (ppt)
- Image Representation and Creation
- Reading: Ch4
|
Jan. 19 - Kernel Operators
- Basics (ppt)
- How to apply kernel? What are the effects?
- What is linear operator?
- How to estimate kernels (mostly, derivative kernels)?
- Intuitive approaches by definition
- By function fitting (optimization)
- As sampled differentiable Gaussian (optimization)
- Edge detectors
- Sobel
- Marr-Hildreth
- Canny (1st derivative, nonmax suppression, hysteresis
thresholding)
- Kernel as basis vectors
- Scale space
|
Jan. 21 - Cont'd
- Readings: Ch5
- Reading: [Marr&Hildreth:80, Sobel:70, Prewitt:70, Canny:86, Frei&Chen:77]
- Assignments: 5.2, 5.4, 5.7, 5.8, 5.11, 5.12, 5.15
|
Jan. 26 - Noise Removal
- Basics (ppt)
- Variable conductance diffusion (The PDE approach)
- Maximum a-posteriori probability (optimization)
- Other modern noise removal algorithms (BM3D, NLM, TV)
|
Jan. 28 - Cont'd
- Readings: Ch6
- Reading: [BM3D:07],[NLM:05],[TV:92],[Besag:86],[Geman&Geman:84]
- Assignments: Choose an image within your research domain and
compare effect using bilateral, adaptive-median, MAP, VCD, BM3D, TV, and NLM
|
| Feb. 2 - Cont'd
|
Feb. 4 - Cont'd
- Advanced Techniques for Denoising by Zhifei (pdf)
|
Feb. 9 - Mathematical Morphology
- Basics (ppt)
- Properties of morphological operators
- Grayscale morphology (with flat s.e.)
- Distance transform
|
Feb. 11 - Cont'd
- Readings: Ch7
- Reading: [Haralick:PAMI87]
- Assignments: choose one (7.2, 7.3, 7.4), 7.5, 7.8, 7.9. Implement
gray-scale morphology and compare the results with those obtained
from denoising (use the same image)
|
Feb. 16 - Segmentation
- Basics (ppt)
- Thresholding [Histogram-based analysis, Otsu's Method (optimization), GMM and EM (optimization)]
- Clustering: color similarity (k-means vs. mean-shift)
- Connected Component Analysis
- Active Contours (Snake vs. Level Sets)
- Watersheds
- Graph Cuts
|
Feb. 18 - Cont'd
- Readings: Ch8
- Reading:
- Assignments:
|
| Feb. 23 - Cont'd
|
Feb. 25 - No Class
|
| Mar. 1 - Parametric Transform
|
Mar. 3 - No Class
|
| Mar. 8 - Cont'd
|
Mar. 10 - Cont'd
|
| Mar. 15 - Spring Break
|
Mar. 17 - Spring Break
|
| Mar. 22 - Shape
|
Mar. 24 - Cont'd
|
| Mar. 29 - Descriptors
|
Mar. 31 - Cont'd
|
| Apr 5 - Matching
|
Apr 7 - Cont'd
|
| Apr 12 - 3D Vision
|
Apr 14 - Cont'd
|
| Apr 19 - TBD
|
Apr 21 - Cont'd
|
| Apr 26 - TBD
|
Apr 28 - Cont'd
|
