Lecture Notes-CLICK ON THE TOPICS TO DOWNLOAD THEM DIRECTLY
- Topic 1. Introduction
- Topic 2. Overview of different image modalities: photo images, video, and 2D-3D-4D medical data
- Topic 3. Overview of basic image processing (point and local neighborhood processing): gamma correction, histogram equalization, window-center adjustment, linear filtering, image gradients.
- Topic 4. Basic image segmentation in 2D (thresholding, region-growing, mean-shift, live-wire).
- Topic 5. Deformable models (snakes): gradient descend, DP-snakes. Also distance transforms and generalized distance transforms.
- Topic 6. Beyond snakes: implicit vs. explicit representation of boundaries, level-sets, geodesic active contours, geometric energy functionals.
- Topic 7. Correspondence, Stereo (Window-based, scan-line based, grid-based), Graph Cuts algorithm for energy minimization on grids.
- Topic 8. Surface extraction in 3D, binary labeling, and graph cuts: volume segmentation, multi-view reconstruction, implicit vs. explicit boundary representation, binary submodular energies, geometric functionals, Markov Random Fields.
- Topic 9. Multi-label image analysis problems: image restoration, stereo, texture synthesis, multi-object segmentation, pair-wise interaction potentials (convex vs. discontinuity preserving), energy minimization algorithms (simulated annealing, ICM, Ishikawa’s algorithm, multi-way graph cuts, a-expansions).