Peak signal-to-blur ratio (PSBR) is a recently introduced measure of detail preservation that aims at overcoming the limitations of the sole peak signal-to-noise ratio (PSNR) and other metrics in evaluating the performance of image denoising filters. Indeed, it is known that image denoising is not a trivial task: the image details should be preserved during noise removal, so accurate measurements of the filtering features are needed in order to validate new filters. This paper presents a novel algorithm for PSBR evaluation that is computationally lighter and more effective than the previous PSBR technique. In particular, the new algorithm does not require any threshold and does not need any offset-correction procedure. Results of computer simulations dealing with images corrupted by Gaussian and impulse noise show that the proposed PSBR yields very accurate measurements and largely outperforms the previous approach and other metrics in the literature.

New Peak Signal-to-Blur Ratio (PSBR) Algorithm for Performance Evaluation of Image Filters

RUSSO, FABRIZIO
2015-01-01

Abstract

Peak signal-to-blur ratio (PSBR) is a recently introduced measure of detail preservation that aims at overcoming the limitations of the sole peak signal-to-noise ratio (PSNR) and other metrics in evaluating the performance of image denoising filters. Indeed, it is known that image denoising is not a trivial task: the image details should be preserved during noise removal, so accurate measurements of the filtering features are needed in order to validate new filters. This paper presents a novel algorithm for PSBR evaluation that is computationally lighter and more effective than the previous PSBR technique. In particular, the new algorithm does not require any threshold and does not need any offset-correction procedure. Results of computer simulations dealing with images corrupted by Gaussian and impulse noise show that the proposed PSBR yields very accurate measurements and largely outperforms the previous approach and other metrics in the literature.
File in questo prodotto:
File Dimensione Formato  
IMAS-07.pdf

Accesso chiuso

Descrizione: articolo principale
Tipologia: Documento in Versione Editoriale
Licenza: Digital Rights Management non definito
Dimensione 1.41 MB
Formato Adobe PDF
1.41 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
REVISED 72602-151 Fabrizio Russo.pdf

Accesso chiuso

Descrizione: revised manuscript submitted
Tipologia: Bozza finale post-referaggio (post-print)
Licenza: Digital Rights Management non definito
Dimensione 1.2 MB
Formato Adobe PDF
1.2 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2844919
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact