Video quality assessment is an important tool of guaranteeing video services in a required level of quality. Although subjective quality assessment is more reliable due to the reflection of Human Visual System (HVS) than objective quality assessment, it is a time-consuming and very expensive approach, and is not appropriate for real-time applications. Therefore, much research has been made for objective video quality assessment instead of subjective video quality assessment.Among three kinds of objective assessment approaches which are full-reference, reduced-reference and no-reference methods, no-reference method has drawn much attention because it does not require any reference. The encoding parameters are good features to use for no-reference model because the encoded bitstreams carry plenty of information about the video contents and it is easy to extract some coding parameters to assess visual quality.In this paper, we propose a no-reference quality metric using two kinds of coding parameters in H.264/AVC: quantization and block mode parameters. These parameters are extracted and computed from H.264/AVC bitstreams, without relying on pixel domain processing. We design a linear quality metric composed of these two parameters. The weight values of the parameters are estimated using linear regression with the results of subjective quality assessment which are obtained based on the DSIS (Double Stimulus Impairment Scale) method of ITU-R BT.500-11.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.