Journal ArticleDOI
A perceptual metric for stereoscopic image quality assessment based on the binocular energy
TLDR
A full reference metric for quality assessment of stereoscopic images based on the binocular fusion process characterizing the 3D human perception is proposed and the difference of binocular energy has shown a high correlation with the human judgement for different impairments and is used to build the Binocular Energy Quality Metric (BEQM).Abstract:
Stereoscopic imaging is becoming very popular and its deployment by means of photography, television, cinema. . .is rapidly increasing. Obviously, the access to this type of images imposes the use of compression and transmission that may generate artifacts of different natures. Consequently, it is important to have appropriate tools to measure the quality of stereoscopic content. Several studies tried to extend well-known metrics, such as the PSNR or SSIM, to 3D. However, the results are not as good as for 2D images and it becomes important to have metrics dealing with 3D perception. In this work, we propose a full reference metric for quality assessment of stereoscopic images based on the binocular fusion process characterizing the 3D human perception. The main idea consists of the development of a model allowing to reproduce the binocular signal generated by simple and complex cells, and to estimate the associated binocular energy. The difference of binocular energy has shown a high correlation with the human judgement for different impairments and is used to build the Binocular Energy Quality Metric (BEQM). Extensive experiments demonstrated the performance of the BEQM with regards to literature.read more
Citations
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Proceedings ArticleDOI
No-reference stereo image quality assessment by learning gradient dictionary-based color visual characteristics
TL;DR: The experimental results show that the proposed no-reference stereo image quality assessment metric always achieves high consistency with human subjective assessment for both symmetric and asymmetric distortions.
Proceedings ArticleDOI
Stereoscopic 3D image quality assessment based on cyclopean view and depth map
TL;DR: Experimental results show that the proposed metric correlates better with human judgement than the state-of-the-art metrics.
Journal ArticleDOI
Perceptual stereoscopic image quality assessment method with tensor decomposition and manifold learning
TL;DR: A new perceptual SIQA method is proposed, which includes two stages: training stage and quality prediction stage, which has better performance and achieves highly consistent alignment with subjective assessment compared with state-of-the-artSIQA metrics.
Journal ArticleDOI
Full-reference quality assessment of stereoscopic images by learning binocular visual properties.
TL;DR: A novel stereoscopic image quality assessment (SIQA) method by jointly considering monocular perception and binocular interaction is proposed and shown to be competitive with the state-of-the-art FR SIQA algorithms.
Journal ArticleDOI
Siamese-Network-Based Learning to Rank for No-Reference 2D and 3D Image Quality Assessment
TL;DR: An index for both no-reference 2D and 3D IQA is presented and a learning to rank model using Siamese convolutional neural networks (LRSN) for quality comparison is proposed.
References
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Image information and visual quality
Hamid R. Sheikh,Alan C. Bovik +1 more
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