Detection of distortion in small moving images, compared to the predictions of a spatio-temporal model

The image sequence discrimination model we use models optical blurring and retinal light adaptation. Two parallel channels, sustained and transient, with different masking rules based on contrast gain control, are used. Performance of the model was studied for two tasks representative of a video communication system with versions of monochrome H.263 compressed images. In the first study, five image sequences constituted pairs of non-compressed and compressed images to be discriminated with a 2-alternative-forced-choice method together witha staircase procedure. The thresholds for each subject were calculated. Analysis of variance showed that the differences between the pictures were significant. The model threshold was close to the average of the subjects for each picture, and the model thus predicted these results quite well. In the second study, the effect of transmission errors on the Internet, i.e, packet losses, wastested with the method of constant stimuli. Both reference and comparison image was distorted. The task of the subjects was to judge whether the presented video quality was worse than the initially seen reference video. Two differentquality levels of the compressed sequences were simulated. The differences inthe thresholds among the different video scenes were to some extent predictedby the model. Category scales indicate that detection of distorsions and overall quality judgements are based on different psychological processes.