An Audio-video Collaborative JND Estimation Model for Multimedia Data

An audio-video collaborative JND estimation model for multimedia data was proposed in this paper by delving into the impact of audio signals on HVS. Firstly, we extract and analyze the temporal perceptual features of audio in terms of loudness, duration, and audio energy. Secondly, the spatial feature of audio is analyzed using audio-guided visual saliency. Based on the temporal and spatial perceptual features of audio, an audio adjustment factor is designed and integrated with a video-based JND model to propose the audio-video collaborative JND estimation model. Detailed performance results of different JND models are shown in Table. 1 . The simulation results validate that the proposed JND model significantly improves the JND estimation accuracy of multimedia data with excellent performance and stronger distortion concealment ability, with strong competitiveness among the state-of-the-art models.