Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method.
Improved TV-CS Approches for Inverse Scattering Problem / Bevacqua, M; Di Donato, L. - In: THE SCIENTIFIC WORLD JOURNAL. - ISSN 1537-744X. - 2015:(2015), pp. 1-9. [10.1155/2015/262985]
Improved TV-CS Approches for Inverse Scattering Problem
Bevacqua M;
2015-01-01
Abstract
Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method.| File | Dimensione | Formato | |
|---|---|---|---|
|
Bevacqua_2015_SWJ_Improved_Editor.pdf
accesso aperto
Descrizione: Versione dell'editore - Open Access
Tipologia:
Versione Editoriale (PDF)
Licenza:
Creative commons
Dimensione
2.33 MB
Formato
Adobe PDF
|
2.33 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
