In-service video quality measurements in optical fiber links based on neural network

Title:

In-service video quality measurements in optical fiber links based on neural network

Creator:

Nasiri-Avanaki , Muhammad-Reza and Ebrahimpour , Reza

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:2e44c31e-11b6-4e43-9de1-a3c2b723608e
uuid:2e44c31e-11b6-4e43-9de1-a3c2b723608e

Subject:

Digital video transmission link, single model optical fibre, no reference video quality metrics, and back propagation neural networks

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Video quality assessment plays a key role in evaluating and optimizing video systems. In this paper, objective image quality metric, appropriate for the fiber optic image transmission line without accessing to the original images, is evaluated by conventional neural networks. It allows an efficient continuous time scoring of the video stream efficiently by a mark on a scale of zero to five. The image database in this research has been collected in the Semnan University. The certainty of the trained network is above 81 percent. Simulation results show that the proposed method is highly correlated with experimental data collected through the subjective experiments.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2007 Volume:17 | Number:5

Harvested from:

CDK

Metadata only:

false