In this paper we propose a new method of image quality assessment for the evaluation of the block distortion through artificial neural networks (ANNs). The approach is new and intends to address the problem of the assessment of the visual quality of compres sed images from an original point of view. ANN's in particular are applied in order to detect the presence of blocking errors inside pre-processed pictures. To this purpose, a new local blockirtg distortion parameter is introduced. Experiments and simulations, even if very preliminary, have confirmed the interest of the proposed approach. A complete formalization of the problem will also be presented.

Block Distortion Assessment for Image Compression Through ANNs

ANGUITA, DAVIDE;RIDELLA, SANDRO
1996

Abstract

In this paper we propose a new method of image quality assessment for the evaluation of the block distortion through artificial neural networks (ANNs). The approach is new and intends to address the problem of the assessment of the visual quality of compres sed images from an original point of view. ANN's in particular are applied in order to detect the presence of blocking errors inside pre-processed pictures. To this purpose, a new local blockirtg distortion parameter is introduced. Experiments and simulations, even if very preliminary, have confirmed the interest of the proposed approach. A complete formalization of the problem will also be presented.
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: http://hdl.handle.net/11567/539165
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact