A continuous bitstream-based blind video quality assessment using multi-layer perceptron

Abstract

We propose a continuous blind/no-reference video quality assessment (NR-VQA) algorithm based on features extracted from the bitstream, i.e., without decoding the video. The resulting algorithm requires minimal training and adopts a simple multi-layer perceptron for score prediction. The algorithm is computationally appealing. To assess the performance of the algorithm, both the Pearson Correlation Coefficient (PCC) and the Spearman Rank Ordered Correlation Coefficient (SROCC) are computed between the predicted values and the quality scores of two databases. The proposed approach is shown to have a high correlation with human visual perception of quality.