No-reference image and video quality assessment: a classification and review of recent approaches
M Shahid, A Rossholm, B Lövström… - EURASIP Journal on …, 2014 - Springer
The field of perceptual quality assessment has gone through a wide range of developments
and it is still growing. In particular, the area of no-reference (NR) image and video quality …
and it is still growing. In particular, the area of no-reference (NR) image and video quality …
Rankiqa: Learning from rankings for no-reference image quality assessment
X Liu, J Van De Weijer… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
We propose a no-reference image quality assessment (NR-IQA) approach that learns from
rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese …
rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese …
Convolutional neural networks for no-reference image quality assessment
In this work we describe a Convolutional Neural Network (CNN) to accurately predict image
quality without a reference image. Taking image patches as input, the CNN works in the …
quality without a reference image. Taking image patches as input, the CNN works in the …
Blind image quality assessment using a general regression neural network
We develop a no-reference image quality assessment (QA) algorithm that deploys a general
regression neural network (GRNN). The new algorithm is trained on and successfully …
regression neural network (GRNN). The new algorithm is trained on and successfully …
Toward a blind deep quality evaluator for stereoscopic images based on monocular and binocular interactions
During recent years, blind image quality assessment (BIQA) has been intensively studied
with different machine learning tools. Existing BIQA metrics, however, do not design for …
with different machine learning tools. Existing BIQA metrics, however, do not design for …
Stereoscopic video quality assessment based on 3D convolutional neural networks
The research of stereoscopic video quality assessment (SVQA) plays an important role for
promoting the development of stereoscopic video system. Existing SVQA metrics rely on …
promoting the development of stereoscopic video system. Existing SVQA metrics rely on …
Blind 3D mesh visual quality assessment using support vector regression
Various visual distortions can inevitably affect the 3D meshes during their transmission and
geometrical processing. In most practical cases, blind quality assessment becomes a …
geometrical processing. In most practical cases, blind quality assessment becomes a …
A strong baseline for image and video quality assessment
S Wen, J Wang - arXiv preprint arXiv:2111.07104, 2021 - arxiv.org
In this work, we present a simple yet effective unified model for perceptual quality
assessment of image and video. In contrast to existing models which usually consist of …
assessment of image and video. In contrast to existing models which usually consist of …
Learning to detect multiple photographic defects
In this paper, we introduce the problem of simultaneously detecting multiple photographic
defects. We aim at detecting the existence, severity, and potential locations of common …
defects. We aim at detecting the existence, severity, and potential locations of common …
[HTML][HTML] Context-dependent image quality assessment of JPEG compressed Mars Science Laboratory Mastcam images using convolutional neural networks
The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires
images that are often JPEG compressed before being downlinked to Earth. Depending on …
images that are often JPEG compressed before being downlinked to Earth. Depending on …