%0 Journal Article
	%A H. El Khattabi and  A. Tamtaoui and  D. Aboutajdine
	%D 2011
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 51, 2011
	%T Video Quality assessment Measure with a Neural Network
	%U https://publications.waset.org/pdf/3381
	%V 51
	%X In this paper, we present the video quality measure
estimation via a neural network. This latter predicts MOS (mean
opinion score) by providing height parameters extracted from
original and coded videos. The eight parameters that are used are: the
average of DFT differences, the standard deviation of DFT
differences, the average of DCT differences, the standard deviation
of DCT differences, the variance of energy of color, the luminance
Y, the chrominance U and the chrominance V. We chose Euclidean
Distance to make comparison between the calculated and estimated
output.
	%P 328 - 332