Several contemporaneous image processing and computer vision systems rely upon the full-
reference image quality assessment (IQA) measures. The single-scale structural similarity …

The growing production of digital content and its dissemination across the worldwide web
require eficient and precise management. In this context, image quality assessment …

Unsupervised single image restoration approach, Deep Image Prior (DIP), aims to restore
images by learning enough raw image statistic priors from the corrupted observation …

Underwater image enhancement has become the requirement for more people to have a
better visual experience or to extract information. However, underwater images often suffer …

Addressing degraded weather conditions plays a vital role in practical applications. Many
existing restoration approaches are limited to specific weather types, which limits their …

Blind image quality assessment (BIQA) of authentically distorted images is a challenging
problem due to the lack of a reference image and the coexistence of blends of distortions …

Identifying distortions in images and videos is important and useful in various visual
applications, such as image quality enhancement and assessment techniques. Instead of …

We propose an anomaly detection based image quality assessment method which exploits
the correlations between feature maps from a pre-trained Convolutional Neural Network …

Due to the characterization capabilities of deep features, image quality assessment (IQA)
methods based on convolutional neural networks (CNNs) have been proposed. However …

Due to the diversity of the degradation process that is difficult to model, the recovery of mixed
distorted images is still a challenging problem. The deep learning model trained under …