Convolutional neural networks (CNNs) are used in an increasingly systematic way in a great variety of computer vision applications, including image quality assessment. However, their application to evaluate the perceived quality of images is strongly limited by the lack of adequate and consistent training data. A CNN-based framework for evaluating image quality of consumer photographs is made up of several building blocks that can be implemented in different ways. In this article, we schematically illustrate how these building blocks have been implemented and combined so far to create feasible solutions that take the most positive characteristics of CNNs while mitigating their intrinsic limitations. Some experimental results are reported to show the effectiveness of CNN-based solutions on real-world image quality datasets.

Celona, L., Schettini, R. (2020). CNN-based image quality assessment of consumer photographs. In London Imaging Meeting 2020: Future Colour Imaging (pp.129-133). Society for Imaging Science and Technology [10.2352/issn.2694-118X.2020.LIM-47].

CNN-based image quality assessment of consumer photographs

Celona, Luigi
;
Schettini, Raimondo
2020

Abstract

Convolutional neural networks (CNNs) are used in an increasingly systematic way in a great variety of computer vision applications, including image quality assessment. However, their application to evaluate the perceived quality of images is strongly limited by the lack of adequate and consistent training data. A CNN-based framework for evaluating image quality of consumer photographs is made up of several building blocks that can be implemented in different ways. In this article, we schematically illustrate how these building blocks have been implemented and combined so far to create feasible solutions that take the most positive characteristics of CNNs while mitigating their intrinsic limitations. Some experimental results are reported to show the effectiveness of CNN-based solutions on real-world image quality datasets.
slide + paper
image quality assessemnt; convolutional neural networks; consumer photographs
English
London Imaging Meeting 2020: Future Colour Imaging
2020
London Imaging Meeting 2020: Future Colour Imaging
2020
2020
1
129
133
none
Celona, L., Schettini, R. (2020). CNN-based image quality assessment of consumer photographs. In London Imaging Meeting 2020: Future Colour Imaging (pp.129-133). Society for Imaging Science and Technology [10.2352/issn.2694-118X.2020.LIM-47].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/10281/292165
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
Social impact