| Monday |
Wednesday |
Friday |
| Mar 24
Introduction:
digital image
gray, color
read and write an image
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Mar 26
Introduction:
digital image
gray, color
read and write an image
functional derivatives
|
Mar 28
conference
HW1: on p.21 of the slides |
| Mar 31
Image Degradation
Image denoising (Chan & Shen 4.5)
|
Apr 2
ROF model
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Apr 4
Numerical implementation for ROF model
HW2 |
| Apr 7
Review of functional space(Gilles ch2.)
strong and weak topology
|
Apr 9
Existence of the minimizer of a functional
make up class: (72 minutes) this Thursday at 5:30pm CH 232
|
Apr 11
Perona and Malik's Nonlinear Diffusion Model (Chan & Shen 4.6.1)
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Apr 14
conference
|
Apr 16
conference
|
Apr 18
conference
|
| Apr 21
Scale-Space Theory (Chan & Shen 4.6.2) |
Apr 23
Motion blur and Out-of-focus blur (Chan & Shen 5.1)
make up class: (72 minutes) this Thursday at 5:30pm CH 232
|
Apr 25
Image Debluring: Code
|
| Apr 28
Shock Filter(Aubert Ch3.3.3)
|
Apr 30
Numerical Scheme for Shock Filter
HW3 |
May 2
conference in SAMSI
|
| May 5
Introduction to image inpainting, interpolation
|
May 7
PDE based image inpainting techniques
linear inpainting via harmonic extension
make up class: this Thursday at 5:30pm SM 1186
|
May 9
Masnou and Morel model for inpainting
TV inpainting modelHW4 |
| May 12
Properties of TV inpainting |
May 14
TV zoom in
Mean and Medium Interpolation
Third order inpainting, Navier-Stokes Equation
make up class: this Thursday at 5:30pm SM 1186
|
May 16
Image Segmentation: Mumford-Shah functional HW5 |
| May 19
Chan-Vese piecewise constant model and its extension
CV piecewise constant Code
|
May 21
Chan-Vese piecewise smooth model |
May 23
Edge based models
HW6 |
| May 26
Memorial Day (no class) |
May 28
Student presentation of final projects |
May 30
Student presentation of final projects |
|
final project:
(a)A New Diffusion-Based Variational Model for Image Denoising and
Segmentation: FANG LI,CHAOMIN SHEN, and LING PI
(b)Image inpainting using a TV-Stokes equation: Xue-Cheng Tai,
Stanley Osher and Randi Holm
(c)A Fast Algorithm for Image Deblurring with Total Variation Regularization: Yilun Wang, Wotao Yin and Yin Zhang
(d)A Multi-resolution Stochastic Level Set Method
for Mumford-Shah Image Segmentation
Yan Nei Law, Hwee Kuan Lee and Andy M. Yip
|
(e)Robust Environmental Image Denoising:
A. Ben Hamza and Hamid Krim
(f)Global Minimization of the Active Contour Model with
TV-Inpainting and Two-phase Denoising:
Shingyu Leung and Stanley Osher
(g)Matting through Variational Inpainting
Kangyu Ni, Sheshadri Thiruvenkadam, and Tony Chan
(h)Extensions to Total Variation Denoising: Peter Blomgren, Tony F. Chan and Pep Mulet
|
(i)An Efficient Operator-Splitting Method for Noise
Removal in Images
D. KRISHNAN, P. LIN and X. C. TAI
(j)A variational approach to reconstructing
images corrupted by Poisson noise
UCLA CAM Report 05-49
Triet Le, Rick Chartrand, and Thomas J. Asaki
(k)Geometric Surface Smoothing via Anisotropic Diffusion of Normals:
Tolga Tasdizen, Ross Whitaker, Paul Burchard, Stanley Osher
(l)On image denoising methods:
Antoni Buades,Bartomeu Coll and Jean Michel Morel
(m)Hybrid geodesic region-based curve evolutions for image
segmentation: Shawn Lanktona, Delphine Nainb, Anthony Yezzia, and Allen Tannenbauma
or pick images related paper on cam report:
http://www.math.ucla.edu/applied/cam/
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