Perceptual image quality assessment (IQA) aims to use computational models to measure
the image quality in consistent with subjective evaluations. Visual saliency (VS) has been …

Most existing blind image quality assessment (BIQA) methods belong to supervised
methods, which always need a large number of image samples and expensive subjective …

No-reference video quality assessment has not been widely benefited from deep learning,
mainly due to the complexity, diversity and particularity of modelling spatial and temporal …

Quality assessment of natural images is influenced by perceptual mechanisms, eg, attention
and contrast sensitivity, and quality perception can be generated in a hierarchical process …

Contrast sensitivity of the human visual system to visual stimuli can be significantly affected
by several mechanisms, eg, vision foveation and attention. Existing studies on foveation …

With rapid development of video acquisition devices and wide applications of video data,
more and more requirements are established to use video data query. video quality …

Image quality assessment models prefer an effective visual feature to perceive image
quality. Structure-based image quality metrics have verified that a measure of structural …

Effective and efficient objective video quality assessment (VQA) methods are highly
desirable in modern visual communication systems for performance evaluation, quality …

Current state-of-the-art video quality assessment (VQA) models typically integrate various
perceptual features to comprehensively represent video quality degradation. These models …

The typical procedure for evaluating the performance of different objective quality metrics
and indices involves comparisons between subjective quality ratings and the quality indices …