In this paper we present a dataset of images to test the performance of image processing algorithms, in particular demosaicing and denoising methods. Despite the plethora of demosaicing and denoising algorithms present in the literature, only few benchmarks are available to test their performance, and most of them are quite old, thus inadequate to represent the images captured by modern devices. The proposed dataset is composed by twenty 16 bit-depth images that can be used to test full-reference image quality metrics. More specifically, twelve pictures have been synthetically created by means of 2D or 3D softwares, while eight images have been captured by a high-end digital camera.

I3D : a new dataset for testing denoising and demosaicing algorithms / C. Bonanomi, S. Balletti, M. Lecca, M. Anisetti, A. Rizzi, E. Damiani. - In: MULTIMEDIA TOOLS AND APPLICATIONS. - ISSN 1380-7501. - (2018 Jul 21). [Epub ahead of print] [10.1007/s11042-018-6396-4]

I3D : a new dataset for testing denoising and demosaicing algorithms

C. Bonanomi
;
M. Anisetti;A. Rizzi;E. Damiani
2018

Abstract

In this paper we present a dataset of images to test the performance of image processing algorithms, in particular demosaicing and denoising methods. Despite the plethora of demosaicing and denoising algorithms present in the literature, only few benchmarks are available to test their performance, and most of them are quite old, thus inadequate to represent the images captured by modern devices. The proposed dataset is composed by twenty 16 bit-depth images that can be used to test full-reference image quality metrics. More specifically, twelve pictures have been synthetically created by means of 2D or 3D softwares, while eight images have been captured by a high-end digital camera.
Image dataset; Demosaicing; Denoising; Image quality
Settore INF/01 - Informatica
21-lug-2018
Article (author)
File in questo prodotto:
File Dimensione Formato  
Bonanomi2018_Article_I3DANewDatasetForTestingDenois.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 2.66 MB
Formato Adobe PDF
2.66 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento 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/2434/585947
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact