Perceptual quality assessment plays a vital role in the visual communication systems owing
to the existence of quality degradations introduced in various stages of visual signal …

Image content variation is a typical and challenging problem in no-reference image-quality
assessment (NR-IQA). This work pays special attention to the impact of image content …

Ranking problems, also known as preference learning problems, define a widely spread
class of statistical learning problems with many applications, including fraud detection …

Omnidirectional image (OI) quality assessment is crucial to facilitate the development of
virtual reality (VR) related technology. In this work, a distortion discrimination assisted multi …

Recently, applying deep learning to no-reference image quality assessment (NR-IQA) has
received significant attention. Especially in the last five years, an increasing interest has …

Due to the 3D spatiotemporal regularities of natural videos and small-scale video quality
databases, effective objective video quality assessment (VQA) metrics are difficult to obtain …

Images acquired by outdoor vision systems easily suffer poor visibility and annoying
interference due to the rainy weather, which brings great challenge for accurately …

Image super-resolution aims to increase the resolution of images with good visual
experience. Over the past decades, there have been many image super-resolution …

Blind image quality assessment (BIQA) for authentic distortions is still a great challenge,
even in today's deep learning era. It has been widely acknowledged that local and global …

In the field of objective image quality assessment (IQA), Spearman's ρ and Kendall's τ, which
straightforwardly assign uniform weights to all quality levels and assume that each pair of …