Temporally Aware Objective Quality Metric for Immersive Video

State-of-the-art objective quality metrics designed for immersive content typically prioritize spatial distortions; therefore, they can omit temporal artifacts introduced by view synthesis and dynamic scene rendering. Consequently, metrics such as the commonly used peak signal-to-noise ratio for immersive video (IV-PSNR) are “temporally blind”, creating a conceptual gap where temporally stable distortions cannot be distinguished from disruptive temporal flickering. To address this limitation, we propose a temporal extension of the IV-PSNR metric that incorporates motion information into the quality assessment process. The method augments the traditional Y, U, and V color components with a fourth channel representing motion vectors (M), enabling the proposed four-component IV-PSNRYUVM metric to account for dynamic distortions introduced by view rendering. To evaluate the effectiveness of the proposed approach, multiple configurations of motion integration were tested, including metrics based solely on motion consistency, metrics combining motion with texture, and several dense optical flow algorithms with different parameter settings. Extensive experiments performed on immersive video sequences demonstrate that the proposed four-component IV-PSNRYUVM achieves the highest correlation with subjectively perceived video quality. These results confirm that combining texture with motion information provides a benefit, making the proposal a valuable addition for real-world immersive video systems.