Advanced image quality assessment approach using multiple quality measures with the artificial neural network data processing support

Karel Fliegel

doi:10.1117/12.675848

18 April 2006 Advanced image quality assessment approach using multiple quality measures with the artificial neural network data processing support

Karel Fliegel

Author Affiliations +

Proceedings Volume 6180, Photonics, Devices, and Systems III; 61801Z (2006) https://doi.org/10.1117/12.675848
Event: Photonics, Devices, and Systems III, 2005, Prague, Czech Republic

Abstract

This paper deals with the subjective and objective image quality evaluation. The demand of an accurate image and video objective quality assessment tool is extremely important in modern multimedia systems. Possible enhancement of the performance in existent image quality assessment approaches using multiple quality measures with the support of the artificial neural network data processing is proposed. The analysis results of the known quality measures and their suitability for the particular image or video quality assessment problem are presented. The most suitable measures are used to implement the novel image quality assessment tool using artificial neural network data processing. Optimization of the proposed model has been done in order to achieve as highest generalization feature of the model as possible. Performance of the implemented model for the image quality assessment has been evaluated using the database of distorted images and subjective image quality assessment results with respect to the Mean Opinion Score (MOS) obtained by the group of observers. It is shown that the proposed image quality assessment model can achieve high correlation with the subjective image quality ratings.

Citation Download Citation

Karel Fliegel "Advanced image quality assessment approach using multiple quality measures with the artificial neural network data processing support", Proc. SPIE 6180, Photonics, Devices, and Systems III, 61801Z (18 April 2006); https://doi.org/10.1117/12.675848

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available