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Variational methods in image processing Week 2

Advanced Course 048926. Variational methods in image processing Week 2. Guy Gilboa. Guy Gilboa – details. Web info: http ://visl.technion.ac.il/~ gilboa/teaching/048926/ Contacts Room: Meyer 955 Phone: 04-829-4653 E-mail: guy.gilboa@ee.technion.ac.il

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Variational methods in image processing Week 2

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  1. Advanced Course 048926 Variational methods in image processingWeek 2 Guy Gilboa

  2. Guy Gilboa – details • Web info: http://visl.technion.ac.il/~gilboa/teaching/048926/ • Contacts • Room: Meyer 955 • Phone: 04-829-4653 • E-mail: guy.gilboa@ee.technion.ac.il • Reception hours: Monday 16:30-17:20, Wednesday 11:00-12:00

  3. Diffusion in real life http://www.youtube.com/watch?v=STLAJH7_zkY

  4. Scale Space for feature extraction

  5. 1D zero-crossing evolution Time t Signal Zero crossing (edges)

  6. SIFT – use of scale spaceScale-invariant feature transform

  7. Linear vs. Nonlinear diffusion P. Perona, J. Malik, “Scale-space and edge detection using anisotropic diffusion”, IEEE Trans. PAMI, 12(7), pp. 629-639, 1990. Noisy input Linear Nonlinear (Perona-Malik)

  8. Tensor diffusion coefficient D • Weickert’s coherence enhancing flow: D is a 2x2 tensor (directional diffusion coefficient) with: • Strong diffusion along the edge. • Weak diffusion across the edge. J. Weickert, “Coherence-enhancing diffusion filtering”, IJCV Vol. 31, pp. 111-127, 1999.

  9. Stereo H. Zimmer, A. Bruhn, L. Valgaerts, M. Breuß, J. Weickert, B. Rosenhahn, H.-P. Seidel:PDE-based anisotropic disparity-driven stereo vision. Vision, Modeling, and Visualization 2008. PDE formulation (with anisotropic diffusion smoothing), very similar to optical flow solutions:

  10. Medical images 3D Ultrasound of10-week old human fetus [from http://www.mia.uni-saarland.de/weickert/demos.html ]

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