Gini Index as Sparsity Measure for Signal Reconstruction from Compressive Samples

Gini Index as Sparsity Measure for Signal Reconstruction from Compressive Samples

Sparsity is a fundamental concept in compressive sampling of signals/images, which is commonly measured using the l 0 norm, even though, in practice, the l 1 or the l p ( 0

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE journal of selected topics in signal processing 2011-09, Vol.5 (5), p.927-932
Hauptverfasser: Zonoobi, D., Kassim, A. A., Venkatesh, Y. V.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Compressive sensing (CS)
Gini index (GI)
Image coding
Image reconstruction
Minimization
Noise
Noise measurement
non-convex optimization
Norms
Optimization
Sampling
Signal processing
Signal reconstruction
simultaneous perturbation stochastic approximation (SPSA)
sparsity measures
Stochasticity
Transforms
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Sparsity is a fundamental concept in compressive sampling of signals/images, which is commonly measured using the l 0 norm, even though, in practice, the l 1 or the l p ( 0
ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2011.2160711