DocumentCode
628730
Title
A novel video quality measurement using ANN
Author
Sunala, S.L. ; Anurenjan, P.R.
Author_Institution
Dept. of Electron. & Commun., Coll. of Eng., Trivandrum, India
fYear
2013
fDate
4-6 June 2013
Firstpage
1
Lastpage
4
Abstract
Measurement of video quality is of fundamental importance to many image and video processing application. Neural network (ANN) is discussed. In this method, we evaluated different videos using both objective and subjective test. Three objective measurements which are Bit rate Structural Similarity Index Method (SSIM) and Interframe Transformation Fidelity (ITF) for different videos are calculated and these measurements are fed to feed forward neural network. The neural network was used to obtain the mapping functions between are objective quality assessment indexes (Mean Opinion Score) and subjective quality assessment Then output score of neural network is compared with Mean Opinion Score (MOS) of the Human Visual system.
Keywords
feedforward neural nets; video signal processing; ANN; ITF; SSIM; bit rate structural similarity index method; feed forward neural network; human visual system; interframe transformation fidelity; mean opinion score; novel video quality measurement; objective measurements; objective quality assessment; subjectivequality assessment; video processing application; video quality measurement; Bit rate; Distortion measurement; Indexes; Neural networks; PSNR; Quality assessment; Video recording; Vidio quality measurement; interframe transformation fidelity artificial neural network; structural similarity index method;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Research Areas and 2013 International Conference on Microelectronics, Communications and Renewable Energy (AICERA/ICMiCR), 2013 Annual International Conference on
Conference_Location
Kanjirapally
Print_ISBN
978-1-4673-5150-8
Type
conf
DOI
10.1109/AICERA-ICMiCR.2013.6575925
Filename
6575925
Link To Document