Blind binocular visual quality predictor using deep fusion network
Blind binocular visual quality prediction (BVQP) is more challenging than blind monocular
visual quality prediction (MVQP). Recently, the application of convolutional neural networks …
visual quality prediction (MVQP). Recently, the application of convolutional neural networks …
Blind stereo image quality assessment inspired by brain sensory-motor fusion
The use of 3D and stereo imaging is rapidly increasing. Compression, transmission, and
processing could degrade the quality of stereo images. Quality assessment of such images …
processing could degrade the quality of stereo images. Quality assessment of such images …
Blind stereo image quality assessment based on binocular visual characteristics and depth perception
Y Chen, K Zhu, L Huanlin - IEEE Access, 2020 - ieeexplore.ieee.org
The quality prediction of stereo images has great challenges without reference images. In
this paper, we propose a novel no-reference stereo image quality assessment (NR-SIQA) …
this paper, we propose a novel no-reference stereo image quality assessment (NR-SIQA) …
No-reference stereo image quality assessment by learning gradient dictionary-based color visual characteristics
In this paper, we propose a no-reference (NR) stereo image quality assessment metric by
learning gradient dictionary-based color visual characteristics. To be specific, firstly, since …
learning gradient dictionary-based color visual characteristics. To be specific, firstly, since …
Bi-disparity sparse feature learning for 3D visual discomfort prediction
Viewing stereoscopic images sometimes causes viewers to feel inconvenience, which is
called 3D visual discomfort. Excessive horizontal disparity, misalignment between the left …
called 3D visual discomfort. Excessive horizontal disparity, misalignment between the left …
Stereo image quality assessment based on sparse binocular fusion convolution neural network
S Li, X Han, M Zubair, S Ma - 2019 IEEE Visual …, 2019 - ieeexplore.ieee.org
In this paper, a sparse binocular fusion convolution neural network is proposed to evaluate
the quality of stereo image. In order to simulate the long-term fusion and processing of the …
the quality of stereo image. In order to simulate the long-term fusion and processing of the …
Reduced-reference stereoscopic image quality assessment using gradient sparse representation and structural degradation
J Ma, G Xu, X Han - IEEE Access, 2021 - ieeexplore.ieee.org
Reduced-reference stereoscopic image quality assessment (RRSIQA) models evaluate
stereoscopic image quality degradation with partial information about the “ideal-quality” …
stereoscopic image quality degradation with partial information about the “ideal-quality” …
Multistage pooling for blind quality prediction of asymmetric multiply-distorted stereoscopic images
Quality prediction for asymmetric multiply-distorted stereoscopic images (MDSIs) confronts
more challenges than previous stereoscopic image quality assessment (SIQA) issues …
more challenges than previous stereoscopic image quality assessment (SIQA) issues …
Information visualization based on visual transmission and multimedia data fusion
L Jiang - International Journal of Information Technologies and …, 2023 - igi-global.com
With the rapid development of information technology, the application media of visual
identity design has been greatly broadened, and the requirements of dynamic variability and …
identity design has been greatly broadened, and the requirements of dynamic variability and …
No-reference stereoscopic image quality assessment guided by visual hierarchical structure and binocular effects
Y Ding, Y Zhao - Applied optics, 2018 - opg.optica.org
Stereoscopic image quality assessment (SIQA) is an essential technique for modern 3D
image and video processing systems serving as performance evaluators and monitors …
image and video processing systems serving as performance evaluators and monitors …