Perceptual image quality assessment: a survey
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 …
to the existence of quality degradations introduced in various stages of visual signal …
An experiment-based review of low-light image enhancement methods
W Wang, X Wu, X Yuan, Z Gao - Ieee Access, 2020 - ieeexplore.ieee.org
Images captured under poor illumination conditions often exhibit characteristics such as low
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …
LR3M: Robust low-light enhancement via low-rank regularized retinex model
Noise causes unpleasant visual effects in low-light image/video enhancement. In this paper,
we aim to make the enhancement model and method aware of noise in the whole process …
we aim to make the enhancement model and method aware of noise in the whole process …
Low-light image enhancement with semi-decoupled decomposition
S Hao, X Han, Y Guo, X Xu… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Low-light image enhancement is important for high-quality image display and other visual
applications. However, it is a challenging task as the enhancement is expected to improve …
applications. However, it is a challenging task as the enhancement is expected to improve …
Learning a no-reference quality assessment model of enhanced images with big data
In this paper, we investigate into the problem of image quality assessment (IQA) and
enhancement via machine learning. This issue has long attracted a wide range of attention …
enhancement via machine learning. This issue has long attracted a wide range of attention …
Blind quality assessment based on pseudo-reference image
Traditional full-reference image quality assessment (IQA) metrics generally predict the
quality of the distorted image by measuring its deviation from a perfect quality image called …
quality of the distorted image by measuring its deviation from a perfect quality image called …
A joint intrinsic-extrinsic prior model for retinex
We propose a joint intrinsic-extrinsic prior model to estimate both illumination and
reflectance from an observed image. The 2D image formed from 3D object in the scene is …
reflectance from an observed image. The 2D image formed from 3D object in the scene is …
No-reference quality metric of contrast-distorted images based on information maximization
The general purpose of seeing a picture is to attain information as much as possible. With it,
we in this paper devise a new no-reference/blind metric for image quality assessment (IQA) …
we in this paper devise a new no-reference/blind metric for image quality assessment (IQA) …
PM₂. ₅ monitoring: use information abundance measurement and wide and deep learning
K Gu, H Liu, Z Xia, J Qiao, W Lin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This article devises a photograph-based monitoring model to estimate the real-time PM 2.5
concentrations, overcoming currently popular electrochemical sensor-based PM 2.5 …
concentrations, overcoming currently popular electrochemical sensor-based PM 2.5 …
Quality evaluation of image dehazing methods using synthetic hazy images
To enhance the visibility and usability of images captured in hazy conditions, many image
dehazing algorithms (DHAs) have been proposed. With so many image DHAs, there is a …
dehazing algorithms (DHAs) have been proposed. With so many image DHAs, there is a …