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Sparsity constrained regularization for multiframe image restoration
Premchandra M. Shankar
, Mark A. Neifeld
Electrical and Computer Engr
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Contribution to journal
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Article
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peer-review
11
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Keyphrases
Expectation-maximization Algorithm
100%
Multi-frame Reconstruction
100%
Linear Minimum Mean Square Error (LMMSE)
100%
Regularization Operator
100%
Sparsity-constrained
100%
Consistency Regularization
100%
Low-resolution Images
100%
Popular
50%
Reconstruction Error
50%
L1-norm
50%
Natural Objects
50%
Maximum a Posteriori Estimation
50%
Undersampling
50%
Wavelet Coefficients
50%
Additive White Gaussian Noise
50%
Multi-frame Super-resolution
50%
Optical Blur
50%
L1-norm Minimization
50%
Generalized Gaussian Density
50%
Minimum Mean Square Error Estimator
50%
Computer Science
Sparsity
100%
Image Restoration
100%
Regularization
100%
Low Resolution Image
100%
Regularization Operator
100%
Reconstruction Error
50%
Additive White Gaussian Noise
50%
Wavelet Coefficient
50%
super resolution
50%
Mathematics
Regularization
100%
Mean Square Error
66%
Gaussian Distribution
33%
Expectation-Maximization Algorithm
33%
Wavelet
33%
Maximum a posteriori estimation
33%
Random Noise
33%