07-06-2012, 05:28 PM
An Object Oriented Approach to Image Restoration in Matlab
An Object Oriented Approach to Image Restoration in Matlab.pdf (Size: 99.91 KB / Downloads: 2)
Regularization by Filtering
One method to choose regularization parameters is:
Generalized Cross Validation
For example, in Tikhonov, choose to minimize
Computational Issues:
1. Choose an appropriate basis for U and V
e.g., singular vectors, Fourier vectors, ...
2. Efficient algorithm (speed and storage) to compute
Iterative Regularization
Some examples:
1. Conjugate Gradient (CG)
2. (Constrained) Steepest Descent (EM-LS)
3. Lucy-Richardson (EM-ML)
To-Do List
• Stopping criteria for iterative methods.
• Better understanding of preconditioning EM-LS.
• Include other regularization by filtering methods.
• Include other iterative regularization methods.
(e.g., Blind Image Restoration – Plemmons, Jefferies)
• Test codes using more real applications.
