Sampling and Reconstruction of Sparse Signals in Shift-Invariant Spaces: Generalized Shannon's Theorem Meets Compressive Sensing.
Tin VlasicDamir SersicPublished in: IEEE Trans. Signal Process. (2022)
Keyphrases
- compressive sensing
- shift invariant
- signal reconstruction
- compressive sampling
- sparse representation
- sparse coding
- signal processing
- random projections
- wavelet domain
- discrete wavelet transform
- rotation invariant
- wavelet coefficients
- compressed sensing
- orthogonal matching pursuit
- image representation
- image classification
- edge preserving
- multiresolution
- random sampling
- multiscale
- blurred images
- dimensionality reduction
- image segmentation
- feature vectors
- image patches
- image features
- super resolution
- face recognition