Quality assessment has been a challenge in the last decade and many issues are still open in this field. An impressive number of full reference metrics dedicated to images have been developed. Many of them are well correlated to human judgment in the framework of multimedia applications. However, only a few metrics have attempted blind (no reference) or semi-blind (reduced reference) image quality assessment. First, because these type of metrics are highly dependent upon the impairment type. Second, it is always difficult to select side information that is both reduced and efficient in representing the original image. These problems increase when dealing with video content, where the temporal variation of both content and quality makes the scope very different from the image one. Furthermore, with the advent of new technologies like 3-D or multiview, quality is facing new challenges since the involvement of the visual perception is increased. Moreover, depth is not only an additional dimension but is also a feature changing the full interpretation of a scene. Therefore, the research community has to improve its understanding of the binocular vision mechanisms such as the binocular rivalry, suppression and fusion, in order to be able to predict the perceptual impact of the various impairments.