东南大学学报（英文版）2021，Vol.37Issue(2)：184-191,8.DOI:10.3969/j.issn.1003-7985.2021.02.008
基于梯度和显著性的无参考模糊图像质量评价方法
No-reference blur assessment method based on gradient and saliency
摘要
Abstract
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 to construct a reference image by blurring a given image.Gradient similarity is included to obtain the gradient distortion measurement map,which can finely reflect the smallest possible changes in textures and details.Second,a saliency model is utilized to calculate image saliency.Specifically,an adaptive method is used to calculate the specific salient threshold of the blurred image,and the blurred image is binarized to yield the salient region map.Block-wise visual saliency serves as the weight to obtain the final image quality.Experimental results based on the image and video engineering database,categorial image quality database,and camera image database demonstrate that the proposed method correlates well with human judgment.Its computational complexity is also relatively low.关键词
无参考图像质量评价/再模糊效应/梯度相似度/显著性Key words
no-reference image quality assessment/reblurring effect/gradient similarity/saliency分类
信息技术与安全科学引用本文复制引用
贾惠珍,雷初聪,王同罕,李潭,伍家松,李广,何剑锋,舒华忠..基于梯度和显著性的无参考模糊图像质量评价方法[J].东南大学学报（英文版）,2021,37(2):184-191,8.基金项目
he National Natural Science Foundation of China(No.61762004,61762005),the National Key Research and Develop-ment 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 Engi-neering Laboratory on Radioactive Geoscience and Big Data Technology(No.JETRCNGDSS201901,JELRGBDT202001,JELRGBDT202003). （No.61762004,61762005）
