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作品数：15被引量：17H指数：3
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Bridge the Gap Between Full-Reference and No-Reference:A Totally Full-Reference Induced Blind Image Quality Assessment via Deep Neural Networks被引量：2
《China Communications》2023年第6期215-228,共14页Xiaoyu Ma Suiyu Zhang Chang Liu Dingguo Yu 
supported by the Public Welfare Technology Application Research Project of Zhejiang Province,China(No.LGF21F010001);the Key Research and Development Program of Zhejiang Province,China(Grant No.2019C01002);the Key Research and Development Program of Zhejiang Province,China(Grant No.2021C03138)。
Blind image quality assessment(BIQA)is of fundamental importance in low-level computer vision community.Increasing interest has been drawn in exploiting deep neural networks for BIQA.Despite of the notable success ach...
关键词：deep neural networks image quality assessment adversarial auto encoder 
No-Reference Blur Assessment Based on Re-Blurring Using Markov Basis
《Intelligent Automation & Soft Computing》2023年第1期281-296,共16页Gurwinder Kaur Ashwani Kumar 
Blur is produced in a digital image due to low passfiltering,moving objects or defocus of the camera lens during capture.Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result...
关键词：Blur score blur variance objective scores re-blurred image subjective scores 
No-Reference Stereo Image Quality Assessment Based on Transfer Learning被引量：1
《Journal of New Media》2022年第3期125-135,共11页Lixiu Wu Song Wang Qingbing Sang 
In order to apply the deep learning to the stereo image quality evaluation,two problems need to be solved:The first one is that we have a bit of training samples,another is how to input the dimensional image’s left v...
关键词：NO-REFERENCE stereo image quality assessment convolution neural network transfer learning phase congruency transformation image fusion 
No-reference noisy image quality assessment incorporating features of entropy, gradient, and kurtosis
《Frontiers of Information Technology & Electronic Engineering》2021年第12期1565-1582,共18页Heng YAO Ben MA Mian ZOU Dong XU Jincao YAO 
Project supported by the National Natural Science Foundation of China(No.61702332);the Zhejiang Provincial Natural Science Foundation of China(Nos.LZY21F030001 and LSD19H180001)。
Noise is the most common type of image distortion affecting human visual perception.In this paper,we propose a no-reference image quality assessment(IQA)method for noisy images incorporating the features of entropy,gr...
关键词：Noisy image quality assessment Noise estimation KURTOSIS Human visual system Support vector regression 
No-reference blur assessment method based on gradient and saliency被引量：2
《Journal of Southeast University(English Edition)》2021年第2期184-191,共8页Jia Huizhen Lei Chucong Wang Tonghan Li Tan Wu Jiasong Li Guang He Jianfeng Shu Huazhong 
The National Natural Science Foundation of China(No.61762004,61762005);the National Key Research and Development Program(No.2018YFB1702700);the Science and Technology Project Founded by the Education Department of Jiangxi Province,China(No.GJJ200702,GJJ200746);the Open Fund Project of Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology(No.JETRCNGDSS201901,JELRGBDT202001,JELRGBDT202003).
To evaluate the quality of blurred images effectively,this study proposes a no-reference blur assessment method based on gradient distortion measurement and salient region maps.First,a Gaussian low-pass filter is used...
关键词：no-reference image quality assessment reblurring effect gradient similarity SALIENCY 
CNN Based No-Reference HDR Image Quality Assessment被引量：4
《Chinese Journal of Electronics》2021年第2期282-288,共7页FAN Kefeng LIANG Jiyun LI Fei QIU Puye 
support by The National Key Research and Development Program of China(No.2019YFB1405503);2019 Public Service Platform of Industrial Technology Foundation of MIIT(No.2019-00895-2-1)。
Motivated by the problems of non-universality and over-reliance on the original reference image in High dynamic range(HDR)Image quality assessment(IQA),a convolutional neural network-based algorithm for no-reference H...
关键词：High dynamic range image Image quality assessment Convolutional neural network Human visual system 
Structured Computational Modeling of Human Visual System for No-reference Image Quality Assessment
《International Journal of Automation and computing》2021年第2期204-218,共15页Wen-Han Zhu Wei Sun Xiong-Kuo Min Guang-Tao Zhai Xiao-Kang Yang 
This work was supported by National Natural Science Foundation of China(Nos.61831015 and 61901260);Key Research and Development Program of China(No.2019YFB1405902).
Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate eval...
关键词：Image quality assessment(IQA) no-reference(NR) structural computational modeling human visual system visual feature extraction 
No-Reference Image Quality Assessment Method Based on Visual Parameters
《Journal of Electronic Science and Technology》2019年第2期171-184,共14页Yu-Hong Liu Kai-Fu Yang Hong-Mei Yan 
supported by the National Natural Science Foundation of China under Grants No.61773094,No.61573080,No.91420105,and No.61375115;National Program on Key Basic Research Project(973 Program)under Grant No.2013CB329401;National High-Tech R&D Program of China(863 Program)under Grant No.2015AA020505;Sichuan Province Science and Technology Project under Grants No.2015SZ0141 and No.2018ZA0138
Recent studies on no-reference image quality assessment (NR-IQA) methods usually learn to evaluate the image quality by regressing from human subjective scores of the training samples. This study presented an NR-IQA m...
关键词：BANDWIDTH human VISUAL system information entropy LUMINANCE NO-REFERENCE image QUALITY assessment (NR-IQA) VISUAL parameter measurement index (VPMI) 
No-reference synthetic image quality assessment with convolutional neural network and local image saliency被引量：2
《Computational Visual Media》2019年第2期193-208,共16页Xiaochuan Wang Xiaohui Liang Bailin Yang Frederick W.B.Li 
sponsored by the National Key R&D Program of China (No. 2017YFB1002702);the National Natural Science Foundation of China (Nos. 61572058, 61472363)
Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, ...
关键词：IMAGE quality assessment SYNTHETIC IMAGE depth-image-based rendering(DIBR) convolutional neural network local IMAGE SALIENCY 
No-Reference Quality Assessment of Enhanced Images
《China Communications》2016年第9期121-130,共10页Leida Li Wei Shen Ke Gu Jinjian Wu Beijing Chen Jianying Zhang 
supported in part by the National Natural Science Foundation of China under Grant 61379143;in part by the Fundamental Research Funds for the Central Universities under Grant 2015QNA66;in part by the Qing Lan Project of Jiangsu Province
Image enhancement is a popular technique,which is widely used to improve the visual quality of images.While image enhancement has been extensively investigated,the relevant quality assessment of enhanced images remain...
关键词：image enhancement quality assessment NO-REFERENCE perceptual feature SVR 
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