Results 11 to 20 of about 1,067,960 (283)
Hybrid No-Reference Quality Assessment for Surveillance Images
Intelligent video surveillance (IVS) technology is widely used in various security systems. However, quality degradation in surveillance images (SIs) may affect its performance on vision-based tasks, leading to the difficulties in the IVS system ...
Zhongchang Ye, Xin Ye, Zhonghua Zhao
doaj +2 more sources
Quadratic Fitting Model in No-Reference Image Quality Assessment [PDF]
The perceptual quality of image is affected by distortions during compression, delivery and storage. Distortions also impact automatic image quality assessment (IQA) that needs to be highly correlated with subjective scores.
A. Gavrovska +4 more
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Domain Fingerprints for No-Reference Image Quality Assessment [PDF]
accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
Weihao Xia 0001 +3 more
openaire +3 more sources
No-reference image quality assessment based on automatic machine learning [PDF]
In different applications in deep learning, due to different required features, it is necessary to design specialized Neural Network structure. However, the design of the structure largely depends on the relevant subject knowledge of researchers and lots
Qian Qi, Sang Qingbing
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No-Reference Quality Assessment of Authentically Distorted Images Based on Local and Global Features
With the development of digital imaging techniques, image quality assessment methods are receiving more attention in the literature. Since distortion-free versions of camera images in many practical, everyday applications are not available, the need for ...
Domonkos Varga
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Video Quality Analysis: Steps towards Unifying Full and No Reference Cases
Video quality assessment (VQA) is now a fast-growing field, maturing in the full reference (FR) case, yet challenging in the exploding no reference (NR) case.
Pankaj Topiwala +4 more
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Degraded Reference Image Quality Assessment
15 pages, 11 figures, 9 ...
Shahrukh Athar, Zhou Wang 0001
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Mask Reference Image Quality Assessment
Understanding semantic information is an essential step in knowing what is being learned in both full-reference (FR) and no-reference (NR) image quality assessment (IQA) methods. However, especially for many severely distorted images, even if there is an undistorted image as a reference (FR-IQA), it is difficult to perceive the lost semantic and ...
Pengxiang Xiao +3 more
openaire +2 more sources
No-Reference Image Quality Assessment Based on a Multitask Image Restoration Network
When image quality is evaluated, the human visual system (HVS) infers the details in the image through its internal generative mechanism. In this process, the HVS integrates both local and global information about the image, utilizes contextual ...
Fan Chen, Hong Fu, Hengyong Yu, Ying Chu
doaj +1 more source
No-Reference Image Quality Assessment Based on Image Multi-Scale Contour Prediction
Accurately assessing image quality is a challenging task, especially without a reference image. Currently, most of the no-reference image quality assessment methods still require reference images in the training stage, but reference images are usually ...
Fan Wang +4 more
doaj +1 more source

