摘要
利用不同偏振方向图像间具有的非局部自相似特征,提出了一种基于稀疏表示的偏振图像超分辨率重建方法.首先用主成分分析训练子字典,其次利用集中稀疏编码方法对图像块进行稀疏分解,最后用稀疏表示系数进行重建.实验结果表明,该方法能有效重建偏振图像中的边缘结构和细节信息.
The non-local self-similarity exists in images with different polarization directions.Therefore a super-resolution reconstruction method was proposed based on sparse representation of polarization images.Firstly,principal component analysis was carried out to train sub-dictionaries.Secondly,centralized sparse coding was used to decompose image blocks sparsely.And finally,sparse representation coefficients were used to reconstruct them.The experimental results demonstrated that the method can effectively reconstruct the edge structure and detail information in polarization images.
作者
张璐璐
麻晓敏
陈松
刘洋
ZHANG Lu-lu;MA Xiao-min;CHEN Song;LIU Yang(Department of Information Technology, Anhui Vocational College of Grain Engineering, Hefei 230011, China;Department of Basic Sciences, Army Artillery and Air Defense Academy, Hefei 230031, China)
出处
《西南师范大学学报（自然科学版）》
CAS
北大核心
2020年第11期99-102,共4页
Journal of Southwest China Normal University(Natural Science Edition)
基金
安徽省教育厅高校优秀青年人才支持计划项目(gxyq2017192)
安徽省教育厅高等学校省级质量工程项目(2017kfk228).
关键词
超分辨率重建
偏振图像
非局部先验知识
稀疏表示
super-resolution reconstruction
polarization image
non-local self-similarity
sparse representation
