Results 21 to 30 of about 4,120 (175)
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges
IEEE Access, 2019 Image quality is important not only for the viewing experience, but also for the performance of image processing algorithms. Image quality assessment (IQA) has been a topic of intense research in the fields of image processing and computer vision.
Yuzhen Niu +4 more
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Journal of Imaging, 2023 Given the reference (distortion-free) image, full-reference image quality assessment (FR-IQA) algorithms seek to assess the perceptual quality of the test image.
Domonkos Varga
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Adaptive No-Reference Image Quality Assessment Based on Multi-Scale Pyramid Pooling [PDF]
Jisuanji gongchengIn the Image Quality Assessment (IQA), no-reference quality assessment methods have demonstrated significant application value and development potential for managing distorted images in real-world scenarios.
WU Xuesong, CHEN Yuanyuan, ZHOU Tao
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Pairwise Learning to Rank for Image Quality Assessment
IEEE Access, 2020 Because the pairwise comparison is a natural and effective way to obtain subjective image quality scores, we propose an objective full-reference image quality assessment (FR-IQA) index based on pairwise learning to rank (PLR).
Yiqing Shi +4 more
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PMT-IQA: Progressive Multi-task Learning for Blind Image Quality Assessment
, 2023 Blind image quality assessment (BIQA) remains challenging due to the diversity of distortion and image content variation, which complicate the distortion patterns crossing different scales and aggravate the difficulty of the regression problem for BIQA.
Pan, Qingyi +4 more
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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.
Lin, Kwan-Yee, Wang, Guanxiang
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Image Quality Assessment by Saliency Maps [PDF]
, 2012 Image Quality Assessment (IQA) is an interesting challenge for image processing applications. The goal of IQA is to replace human judgement of perceived image quality with a machine evaluation. A large number of methods have been proposed to evaluate the
ARDIZZONE, Edoardo, BRUNO, Alessandro
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ARET-IQA: An Aspect-Ratio-Embedded Transformer for Image Quality Assessment
Electronics, 2022 Image quality assessment (IQA) aims to automatically evaluate image perceptual quality by simulating the human visual system, which is an important research topic in the field of image processing and computer vision. Although existing deep-learning-based IQA models have achieved significant success, these IQA models usually require input images with a ...
Hancheng Zhu +5 more
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No-reference quality assessment for image-based assessment of economically important tropical woods.
PLoS ONE, 2020 Image Quality Assessment (IQA) is essential for the accuracy of systems for automatic recognition of tree species for wood samples. In this study, a No-Reference IQA (NR-IQA), wood NR-IQA (WNR-IQA) metric was proposed to assess the quality of wood images.
Heshalini Rajagopal +3 more
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No-Reference Image Quality Assessment with Convolutional Neural Networks and Decision Fusion
Applied Sciences, 2021 No-reference image quality assessment (NR-IQA) has always been a difficult research problem because digital images may suffer very diverse types of distortions and their contents are extremely various.
Domonkos Varga
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