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adaptive TVMM demo
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adaptive TVMM demo The following programme can be provided in order to overwrite the internal ones. Recall that, by default, all calculations are performed with circular convolutions. (see Technical Report)
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train_ensemble.tar
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train_ensemble.tar The Following Code in the following region creates data to be separated. Replace with your own data if required. Model is D=A*s Variables required
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Deblurring Images - Matrices, Spectra, and Filteri
4.0
This script demonstrates some basics of how to read and display images in MATLAB using Deblurring Images - Matrices, Spectra, and Filtering.
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Noise Reduction for Magnetic Resonance
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Please read the following description if you use this code for research purpose:
Noise Reduction for Magnetic Resonance Images via Adaptive Multiscale Products Thresholding.
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interintra
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This code can only be used for research purpose only.
You need Matlab Wavelet Toolbox to run the code.
In this code, we suppose the input image is a nxn square matrix (just for some convenience:).
You may easily revise the code for non-square nxm images.
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otimization problem
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This algorithm solves the otimization problem
min_x \| y - A x \|_2^2 + lambda Phi(x)
and has applications in compressed sensing, image restoration
and reconstruction, sparse regression, and several other problems.
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Point-wise adaptive window size estimation
4.0
Point-wise adaptive window size estimation for masked and full neighbourhood
Pointwise linear LPA with the ICI adaptive window sizes is used for the pixel wise filtering;
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Fast Total Variation Deconvolution
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Fast Total Variation Deconvolution
In this version, we implemented the Alternating Direction Method (ADM),
this version avoids the ill-conditioning caussed by
large penalty paramter by considering the augmented Lagrangian and ADM.
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KernelBasedDeblurringToolBox_ver1
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KernelBasedDeblurringToolBox_ver1
This simulation example demonstrates the kernel regression-based deblurring method with the steering kernel function, and this generates the deblurred image of Fig in the paper "Deblurring Using Locally-Adaptive Kernel regression.
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The denoised image by iterative steering kernel re
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The denoised image by iterative steering kernel regression
A film grain removal example by iterative steering kernel regression
pilot estimation by second order classic kernel regression
iteartive steering kernel regression (second order)
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