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Stable and robust sampling strategies for compressive imaging
Felix Krahmer
, Rachel Ward
Georg August Universität Göttingen
University of Texas at Austin
Research output
:
Contribution to journal
›
Article
›
peer-review
120
Scopus citations
Overview
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Dive into the research topics of 'Stable and robust sampling strategies for compressive imaging'. Together they form a unique fingerprint.
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Keyphrases
Sampling Strategy
100%
Compressive Imaging
100%
Local Coherence
60%
Image Reconstruction
40%
Wavelet
40%
Sparsity Basis
40%
Lower Order
40%
Variable Density Sampling
40%
Transform Domain
20%
Sparsity
20%
Compressed Sensing Theory
20%
Total Variation Regularization
20%
Power Law
20%
Noise Measurement
20%
Sparse Recovery
20%
Finite Difference
20%
Near-optimal
20%
Signal Processing Applications
20%
Order Frequency
20%
Haar Wavelet
20%
Embedding Dimension
20%
Restricted Isometry Property
20%
Fourier Measurements
20%
Fourier Transform Domain
20%
Sample Reconstruction
20%
Average Coherence
20%
Optimal Embeddings
20%
Sensing Vector
20%
Wavelet Transform Domain
20%
Wavelet Sparsity
20%
Engineering
Sparsity
100%
Image Reconstruction
50%
Sampling Density
50%
Frequency Domain
25%
Measurement Noise
25%
Inverse Square
25%
Embedding Dimension
25%
Restricted Isometry Property
25%
Compressive Sensing
25%
Total Variation
25%
Signal Processing Application
25%
Fourier Transform
25%
Mathematics
Wavelet
100%
Matrix (Mathematics)
33%
Total Variation
33%
Haar Wavelet
33%
Processing Application
33%
Power Law
33%
Finite Difference Method
33%
Frequency Domain
33%
Fourier Transform
33%
Signal Processing
33%
Computer Science
Sparsity
100%
Image Reconstruction
50%
Sampling Density
50%
Fourier Transform
25%
Compressive Sensing
25%
Transform Domain
25%
Signal Processing Application
25%
Frequency Domain
25%
Total Variation
25%
Measurement Noise
25%
Earth and Planetary Sciences
Wavelet
100%
Image Reconstruction
50%
Power Law
25%
Noise Measurement
25%
Signal Processing
25%