A quality evaluation model for calculating block and blur effects generated by H.264 and MPEG2 codecs

Many factors can affect and/or compromise the quality of visual media. Most video compression standards use motion compensation and block-based encoding scheme for compression. As a result, the decoded video is altered by one or more compression artifacts, such as block effect, blur, color bleeds, buzzing, false edges, jagged motion and flickering chrominance. In this framework, we present in this paper a quality prediction model for video encoders. Our model is designed to calculate the distortions of blocking and blurring effects, which appeared from the coding operation. We also give an overall score of the two distortions. The validation of our model is done using the subjective video database “LIVE” to correlate with the judgment of the observers. Correlation indicators such as the Spearman rank correlation coefficient (SROCC) and the Pearson linear correlation coefficient (PLCC) indicate that our model gives good performance.