No-Reference Image Quality Assessment and Application Based on Spatial Domain Coding

被引:6
|
作者
Chen Yong [1 ]
Fang Hao [1 ]
Liu Huanlin [2 ]
机构
[1] Chongqing Univ Posts & Telecommun, Key Lab Ind Internet Things & Network Control, Minist Educ, Chongqing 400065, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Sch Telecommun & Informat Engn, Chongqing 400065, Peoples R China
来源
IEEE ACCESS | 2018年 / 6卷
关键词
Local binary patterns; no-reference image quality assessment; neural network; INFORMATION; STATISTICS;
D O I
10.1109/ACCESS.2018.2875951
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aiming at the problem that a no-reference (NR) image quality assessment algorithm is not accurate enough to predict the image quality at present, we proposed a method of NR image quality assessment based on spatial domain coding (SDC). We extracted the spatial structure features of the image on different bit planes. The extracted features quantify the structural information between pixels, which can more accurately reflect the distortion degree of the image. We used a neural network to establish an image quality assessment model. The experimental results show that the proposed image assessment algorithm is more accurate than the existing mainstream image quality assessment algorithms and highly consistent with subjective perception of human eyes. Finally, the proposed algorithm is applied to the auto focus of the camera verifying the practicability and accuracy of the algorithm.
引用
收藏
页码:60456 / 60466
页数:11
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