A no-reference video quality assessment based on Laplacian pyramids

This paper presents an approach to predict the quality of compressed videos with content of natural scenes. The method is focused on measuring the distortion of compressed video without reference. There are two main steps of the proposed method: measuring distortion and predicting video quality. Each frame of the distorted video sequence is first decomposed to an N-subband Laplacian pyramid, then their intra-subband and inter-subband statistical features are fully exploited. Three intra-subband features and three inter-subband features are taken as inputs of the prediction model. Its output is a single score as the predicted video quality. The performance of the proposed method is evaluated on the LIVE video database and the LIVE mobile video database. Results show that the predicted quality scores are well correlated with the mean opinion scores associated to the subjective assessment.