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
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;
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
DOI :
10.1109/AICERA-ICMiCR.2013.6575925