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Image Noise Level Classification Technique Based on Image Quality Assessment
Luo, Geng1; Zhao ZC(赵梓成)2; Long Q(龙潜)2; Lv, Chun1; Bao, Jie1
会议录名称Proceedings of 2020 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2020
2020-07
页码651-656
DOI10.1109/ICPICS50287.2020.9202118
产权排序第2完成单位
收录类别EI
会议名称2020 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2020
会议日期2020-07-28
会议地点Shenyang, China
摘要

Image noise plays a vital role in digital image processing. However, in some specific application scenarios, random noise has an uncontrollable effect on digital image processing. Besides, a large number of hyper parameters which need to be fine-tuned can lead to inefficient projects. Therefore, we propose a Image Noise Level Classification(INLC) technique for specific application scenarios by comparing image quality assessment(IQA) methods, fitting curves and designing two neural networks. For low-accuracy, we come up with a soft way by setting a tolerance rate to achieve a higher acceptable accuracy. Experiments show that our INLC is more accurate and efficient.

资助项目N/A
项目资助者N/A
语种英语
学科领域计算机科学技术
学科门类工学 ; 工学::计算机科学与技术(可授工学、理学学位)
文章类型Conference article (CA)
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN号9781728198736
EI入藏号20204309378098
EI主题词Image quality
EI分类号723.4 Artificial Intelligence - 921.6 Numerical Methods
引用统计
文献类型会议论文
条目标识符http://ir.ynao.ac.cn/handle/114a53/23721
专题南方基地
作者单位1.Chengdu Fourier Electronic Technology Co., Ltd, R and D Department, Chengdu, China
2.Yunnan Observatories, Chinese Academy of Science, Kunming, China
推荐引用方式
GB/T 7714
Luo, Geng,Zhao ZC,Long Q,et al. Image Noise Level Classification Technique Based on Image Quality Assessment[C]:Institute of Electrical and Electronics Engineers Inc.,2020:651-656.
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