Results 11 to 20 of about 896 (171)
Effectiveness and clinical impact of using deep learning for first-trimester fetal ultrasound image quality auditing [PDF]
BMC Pregnancy and ChildbirthBackground Regular auditing of ultrasound images is required to maintain quality; however, manual auditing is time-consuming and can be inconsistent. We therefore aimed to develop and validate an artificial intelligence-based image quality audit (AI-IQA)
Xiaoyan Cao +13 more
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On optimisation of Paganin's method for propagation-based X-ray phase-contrast imaging and tomography. [PDF]
J MicroscAbstract Paganin's method for image reconstruction in propagation‐based phase‐contrast X‐ray imaging and tomography has enjoyed broad acceptance in recent years, with over one thousand publications citing its use. The present paper discusses approaches to optimisation of the method with respect to simple image quality metrics, such as signal‐to‐noise ...
Gureyev TE +3 more
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No-Reference Image Quality Assessment Model Based on Generated Perceptual Difference [PDF]
Jisuanji gongcheng, 2021 The visual perception difference in the Human Visual System(HVS) is key to image quality evaluation.By sensing the visual difference between the distorted image and the reference image,the distortion degree of the image can be judged.However,this method ...
LIU Hai, YANG Huan, PAN Zhenkuan, HUANG Baoxiang, HOU Guojia
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Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Accepted to IEEE/CVF CVPR 2023. Code will be released post conference in July 2023.
Avinab Saha +2 more
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TIQA-PSI: Toolbox for perceptual Image Quality Assessment of Pan-Sharpened Images
SoftwareX, 2023 A Pan-Sharpening (PS) technique integrates spatial details of a high-resolution panchromatic (PAN) image with spectral information of a low-resolution multi-spectral (MS) image, creating a single high-resolution color image.
Igor Stępień, Mariusz Oszust
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No-Reference Image Quality Assessment Based on Dual-Domain Feature Fusion
Entropy, 2020 Image quality assessment (IQA) aims to devise computational models to evaluate image quality in a perceptually consistent manner. In this paper, a novel no-reference image quality assessment model based on dual-domain feature fusion is proposed, dubbed ...
Yueli Cui
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Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 No-reference image quality assessment (NR-IQA) is a fundamental yet challenging task in low-level computer vision community. The difficulty is particularly pronounced for the limited information, for which the corresponding reference for comparison is typically absent.
Kwan-Yee Lin, Guanxiang Wang
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Journal of Imaging, 2022 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 evaluate the perceptual quality of digital images consistent with human quality ...
Domonkos Varga
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Conv-Former: A Novel Network Combining Convolution and Self-Attention for Image Quality Assessment
Sensors, 2022 To address the challenge of no-reference image quality assessment (NR-IQA) for authentically and synthetically distorted images, we propose a novel network called the Combining Convolution and Self-Attention for Image Quality Assessment network (Conv ...
Lintao Han +6 more
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Goal oriented image quality assessment
IET Image Processing, 2022 The area of image quality assessment(IQA) is an active research area in image processing and computer vision. All IQA algorithms reported in literature are attempting to quantify only the visual quality of the images/videos. An interesting question to be
Kiruthika S., Dr. Masilamani V.
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