Stereo Image Quality Assessment Based on Top-Down Visual Mechanism

In order to improve the consistency of metrics between the objective assessment and the human subjective evaluation of stereo image quality, inspired by the top-down mechanism of human vision, this paper proposes a stereo attention-based no-reference stereo image quality assessment method. In the proposed stereo attention module. First, the amplitude of binocular response is adaptively adjusted by the energy coefficient in the proposed binocular fusion module, and the binocular features are processed simultaneously in the spatial and channel dimensions. Second, the proposed binocular modulation module realizes the top-down modulation of the high-level binocular information to the low-level bino- and monocular information simultaneously. In addition, the dual-pooling strategy proposed in this paper processes the binocular fusion map and binocular difference map to obtain the critical information that is more conducive to quality score regression. The performance of the proposed method is validated based on the publicly available LIVE 3D and WIVC 3D databases. The experimental results show that the proposed method achieves high consistency between objective assessment indices and labels.