MATLAB PROJECT
Dual-Stream
Interactive Networks for No-Reference Stereoscopic Image Quality Assessment
Abstract:
The goal of objective stereoscopic image quality assessment (SIQA) is to
predict the human perceptual quality of stereoscopic/3D images automatically
and accurately. Compared with traditional 2D image quality assessment, the
quality assessment of stereoscopic images is more challenging because of
complex binocular vision mechanisms and multiple quality dimensions. In this
paper, inspired by the hierarchical dual-stream interactive nature of the human
visual system, we propose a stereoscopic image quality assessment network
(StereoQA-Net) for no-reference stereoscopic image quality assessment. The
proposed StereoQA-Net is an end-to-end dual-stream interactive network
containing left and right view sub-networks, where the interaction of the two sub-networks
exists in multiple layers. We evaluate our method on the LIVE stereoscopic
image quality databases. The experimental results show that our proposed
StereoQA-Net outperforms state-of-the-art algorithms on both symmetrically and
asymmetrically distorted stereoscopic image pairs of various distortion types.
In a more general case, the proposed StereoQA-Net can effectively predict the
perceptual quality of local regions. In addition, cross-dataset experiments
also demonstrate the generalization ability of our algorithm.
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