In this paper, a full-reference image quality assessment (FR-IQA) model based on deep
meta-learning and Conformer is proposed. We combine the Conformer architecture with a …

Digital images can be distorted or contaminated by noise in various steps of image
acquisition, transmission, and storage. Thus, the research of such algorithms, which can …

Research and development of image quality assessment (IQA) algorithms have been in the
focus of the computer vision and image processing community for decades. The intent of IQA …

The objective image quality assessment (IQA) method was developed to replace subjective
observer image quality evaluations in various applications. A reliable full reference color IQA …

Image quality assessment (IQA) model is designed to measure the image quality in
consistent with subjective ratings by computational models. In this research, a valid no …

Objective image quality assessment (IQA) measures are playing an increasingly important
role in the evaluation of digital image quality. New IQA indices are expected to be strongly …

Image quality assessment (IQA) has a vital issue in image processing to measure the
perceptual quality of the image. This aims at the human visual system (HVS) by viewing for …

The integrated OWC‐PON architecture has a potential to overcome the limitations of existent
RF technology and eliminate the last mile bottleneck in geographically constrained access …

Given the reference (distortion-free) image, full-reference image quality assessment (FR-
IQA) algorithms seek to assess the perceptual quality of the test image. Over the years, many …

Significant progress has been made in recent years in image quality assessment (IQA). In
particular, the development of deep learning has provided no-reference (NR)-IQA with more …