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IEEE Final Year Project Topics for CSE

Base Paper Title

Dual-Stream Interactive Networks for No-Reference Stereoscopic Image Quality Assessment

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IEEE Project 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 (2D IQA), 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 (HVS),we propose a Stereoscopic Image Quality Assessment Network(Stereo QA-Net) for No-Reference stereoscopic image quality assessment (NR-SIQA). The proposed Stereo QA-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. Experimental results show that our proposed Stereo QA-Net outperforms state-of-the-art algorithms on both symmetrically and asymmetrically distorted stereoscopic image pairs of various distortion types. And in a more general case, the proposed Stereo QA-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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