[HTML][HTML] CN-BSRIQA: Cascaded network-blind super-resolution image quality assessment
High resolution (HR) images consist of higher quality and more detail information in
comparison to low-resolution images. But obtaining HR images entails higher costs and …
comparison to low-resolution images. But obtaining HR images entails higher costs and …
Perception-and-cognition-inspired quality assessment for sonar image super-resolution
Due to the light-independent imaging characteristics, sonar images play a crucial role in
fields such as underwater detection and rescue. However, the resolution of sonar images is …
fields such as underwater detection and rescue. However, the resolution of sonar images is …
Super-resolution image visual quality assessment based on structure–texture features
Assessing the visual quality of super-resolution images (SRIs) is crucial for advancing
algorithm development, but it remains an unsolved problem. In this paper, we present a …
algorithm development, but it remains an unsolved problem. In this paper, we present a …
A survey of super-resolution image quality assessment
L Shu, Q Zhu, Y He, W Chen, J Yan - Neurocomputing, 2024 - Elsevier
Image super-resolution (SR) technology plays a crucial role in enhancing image resolution
and has found extensive applications in areas such as medical imaging, surveillance, and …
and has found extensive applications in areas such as medical imaging, surveillance, and …
A database and model for the visual quality assessment of super-resolution videos
Video super-resolution (SR) has important real world applications such as enhancing
viewing experiences of legacy low-resolution videos on high resolution display devices …
viewing experiences of legacy low-resolution videos on high resolution display devices …
Perception-Driven Similarity-Clarity Tradeoff for Image Super-Resolution Quality Assessment
Super-Resolution (SR) algorithms aim to enhance the resolutions of images. Massive deep-
learning-based SR techniques have emerged in recent years. In such case, a visually …
learning-based SR techniques have emerged in recent years. In such case, a visually …
Deep bi-directional attention network for image super-resolution quality assessment
There has emerged a growing interest in exploring efficient quality assessment algorithms
for image super-resolution (SR). However, employing deep learning techniques, especially …
for image super-resolution (SR). However, employing deep learning techniques, especially …
TADSRNet: A triple-attention dual-scale residual network for super-resolution image quality assessment
X Quan, K Zhang, H Li, D Fan, Y Hu, J Chen - Applied Intelligence, 2023 - Springer
Image super-resolution (SR) has been extensively investigated in recent years. However,
due to the absence of trustworthy and precise perceptual quality standards, it is challenging …
due to the absence of trustworthy and precise perceptual quality standards, it is challenging …
Fine-grained image quality assessment: A revisit and further thinking
Image quality assessment (IQA) plays a central role in many image processing algorithms
and systems. Although many popular IQA models achieves high performance on existing …
and systems. Although many popular IQA models achieves high performance on existing …
Face Super-Resolution Quality Assessment Based On Identity and Recognizability
Face Super-Resolution (FSR) plays a crucial role in enhancing low-resolution face images,
which is essential for various face-related tasks. However, FSR may alter individuals' …
which is essential for various face-related tasks. However, FSR may alter individuals' …