首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于e~0范数优化算法的图像重建
引用本文:郭艳清,苏晓蕾,廖亮,刘萍,王新强.基于e~0范数优化算法的图像重建[J].成都大学学报(自然科学版),2014(2):141-144.
作者姓名:郭艳清  苏晓蕾  廖亮  刘萍  王新强
作者单位:中原工学院电子信息学院,河南郑州451191
摘    要:为了解决稀疏信号的重建问题提出了光滑e0范数优化算法,它与最小1范数优化算法等图像重建的方法相比有很大的不同,着重实验了这种信号重建算法中重要参数的选择,并利用手写体数字图像库为试验样本做了一维信号重建和二维图像重建实验.实验结果证明了基于e0范数优化算法在图像重建时间和重建精度上的优越性,此为后续的图像工程研究奠定了基础.

关 键 词:压缩感知  图像重建  稀疏信号重建  e范数优化

Image Reconstruction Based On e0 Norm Optimization Algorithm
GUO Yanqing,SU Xiaolei,LIAO Liang,LIU Ping,WANG Xinqiang.Image Reconstruction Based On e0 Norm Optimization Algorithm[J].Journal of Chengdu University (Natural Science),2014(2):141-144.
Authors:GUO Yanqing  SU Xiaolei  LIAO Liang  LIU Ping  WANG Xinqiang
Institution:(School of Electric and Information Engineer, Zhongyuan University of Technology, Zhengzhou 451191, China)
Abstract:In order to solve the problem of sparse signal reconstruction, this paper proposes a smooth norm optimization algorithm,which is different from the minimum 1 norm optimization algorithm. This paper mainly studies the choice of important parameters in this signal reconstruction algorithm. Taking the handwritten digital image hbraly of the United States Postal Service(USPS) as test samples, we make one-dimensional signal reconstruction and two-dimensional image reconstruction experiments. The experimental results show the advantage of the norm algorithm in image reconstruction precision and reconstruction time, which lays the theoretical foundation for subsequent research on image engineering.
Keywords:compressed sensing  image reconstruction  sparse signal reconstruction  eo norm optimization
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号