摘要
为解决超分辨率成像技术中图像数据传输与重构效率较低等问题,提出基于分布式压缩感知算法研究新的超分辨率成像方法。首先,基于压缩感知算法压缩成像编码孔径,构建分布式压缩感知编码孔径模型,采用多值模板设计编码孔径;其次,基于IOMPI算法重构超分辨率图像。最后,采用空间光调制器对行、列分布的图像子块进行多次压缩感知采样测量,进行、列两种方式图像重构,取其均值为最终重构图像。实验结果表明:基于分布式压缩感知算法的超分辨率成像技术有效缩短图像重构用时最短为9.06 s,提高了重构效率,重构的图像信噪比在0.75以上,细节清晰、无模糊现象。
In order to solve the problem of low efficiency of image data transmission and reconstruction in super-resolution imaging technology,a new super-resolution imaging method based on distributed compressed sensing algorithm is proposed.Firstly,a distributed compressed sensing coding aperture model is constructed based on compressed sensing algorithm to compress the image coding aperture,and a multi-value template is used to design coding aperture.Secondly,the super-resolution image is reconstructed based on IOMPI algorithm.the row and column sub-blocks are sampled by spatial light modulator for multiple compressed sensing measurements,Finally,the spatial light modulator is used to measure the image sub-blocks of row and column distribution by compressed sensing for several times,and image reconstruction is carried out in row and column modes.The average value is taken as final recon-structed image.The experimental results show that super-resolution imaging technology based on distributed com-pressed sensing algorithm can effectively shorten image reconstruction time to 9.06s,and improve reconstruction efficiency.The reconstructed image has a signal-to-noise ratio of more than 0.75,clear details and no ambiguity.
作者
李慧慧
李俊丽
LI Huihui;LI Junli(Taiyuan University,Taiyuan 030024,China;Jinzhong University,Yuci Shanxi 030619,China)
出处
《激光杂志》
北大核心
2020年第6期160-164,共5页
Laser Journal
基金
山西省教育科学"十三五"规划(No.GH-18091)。
关键词
分布式
压缩感知
编码孔径
超分辨率
IOMPI算法
成像
distributed
compressed sensing
coding aperture
super-resolution
IOMPI algorithm
imaging
