A Systematic Review of Medical Image Quality Assessment. [PDF]
J ImagingHerath HMSS +3 more
europepmc +1 more source
Malaria RDT (mRDT) interpretation accuracy by frontline health workers compared to AI in Kano state, Nigeria. [PDF]
BMC Digit HealthFrade S +9 more
europepmc +1 more source
MDFN: Enhancing Power Grid Image Quality Assessment via Multi-Dimension Distortion Feature. [PDF]
Sensors (Basel)Chen Z, Du J, Li J, Lv H.
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Deep blind image quality assessment by employing FR-IQA
2017 IEEE International Conference on Image Processing (ICIP), 2017In this paper, we propose a convolutional neural network (CNN)-based no-reference image quality assessment (NR-IQA). Though deep learning has yielded superior performance in a number of computer vision studies, applying the deep CNN to the NR-IQA framework is not straightforward, since we face a few critical problems: 1) lack of training data; 2 ...
Sanghoon Lee, Jongyoo Kim
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QL-IQA: Learning distance distribution from quality levels for blind image quality assessment
Signal Processing: Image Communication, 2022Abstract Recently, blind image quality assessment (BIQA) has been intensively studied with deep learning. However, the limited quality-annotated datasets restrict its further development. Although patch-based methods have been leveraged to generate more training data, they usually assign the image quality score to all patches in an image ...
Shiguang Liu, Ziqing Huang
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LG-IQA: Integration of local and global features for no-reference image quality assessment
Displays, 2022Xiaodong Bi, Cheng-Yang Du
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Illumination Classification based on No-Reference Image Quality Assessment (NR-IQA)
Proceedings of the 2019 Asia Pacific Information Technology Conference, 2019In this paper, we propose an approach to categorize an image's illumination using no-reference image quality assessment metric (NR-IQA). Two NR-IQA metric (image entropy (IE) and standard deviation (SD), and mean of the pixel value (Mean) were used to categorize the illumination.
Syed Mohd Zahid Syed Zainal Ariffin +1 more
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BN-IQA: A Rapid Image Quality Assessment based on Blue Noise Dithering
2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW), 2019A simplistic full reference image quality assessment (IQA) based on digital halftone (DH) technique is proposed. The method exploits the properties of ordered dithering screens of digital halftoning and attempt to capture the quality degradation by evaluating its halftone output.
Jing-Ming Guo, S. Sankarasrinivasan
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Development of Image Quality Assessment (IQA) For Haze Prediction
Proceedings of International Conference on Artificial Life and Robotics, 2023Rajagopal, Heshalini +4 more
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Fscope-IQA: A Novel Attention Design for Image Quality Assessment
2023 8th International Conference on Communication, Image and Signal Processing (CCISP), 2023Jing Wen, Ling Zhong, Xiaofang Gao
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