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An Object Oriented Approach to Image Restoration in Matlab
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An Object Oriented Approach to Image Restoration in Matlab

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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.
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