计算机工程 ›› 2018, Vol. 44 ›› Issue (5): 205-208.doi: 10.19678/j.issn.1000-3428.0046937

• 图形图像处理 • 上一篇    下一篇

循环移位正交系数的测量矩阵改进算法

安冬冬,龚晓峰,陈思南   

  1. 四川大学 电气信息学院,成都 610065
  • 收稿日期:2017-04-24 出版日期:2018-05-15 发布日期:2018-05-15
  • 作者简介:安冬冬(1992—),女,硕士研究生,主研方向为数字图像处理、检测技术与自动化装置;龚晓峰,教授、博士;陈思南,硕士研究生。
  • 基金项目:
    国家自然科学基金(61473198)。

Improved Measurement Matrix Algorithm of Cyclic Shift Orthogonal Coefficient

AN Dongdong,GONG Xiaofeng,CHEN Sinan   

  1. College of Electrical Engineering and Information Technology,Sichuan University,Chengdu 610065,China
  • Received:2017-04-24 Online:2018-05-15 Published:2018-05-15

摘要: 图像压缩感知中测量矩阵的相关性直接影响重构性能。压缩比与重构性能成正比,压缩比越小,对测量矩阵和重构算法的要求越高。针对压缩比小于0.5的情况,基于正交基线性表示确定性测量矩阵,提出遍历查找的方法,从而打破哈达玛矩阵对被测量信号维数的限制,并给出一种基于循环移位法构造正交系数的改进算法来构造确定性测量矩阵。仿真结果表明,该算法重构的峰值信噪比高于高斯随机测量矩阵和伯努利随机测量矩阵。

关键词: 压缩感知, 测量矩阵, 相关性, 循环移位, 正交系数, 哈达玛矩阵

Abstract: In compressed sensing,the coherence of the measurement matrix directly affects the performance of the reconstruction.Compression ratio is proportional to the reconstruction performance.The requirements for measurement matrix and reconstruction algorithm decrease with the compression ratio.In the case where the compression ratio is less than 0.5,this paper proposes a traverse search method,which is based on orthogonal basis linear representation of deterministic measurement matrices,and breaks the limit of the signal dimension in Hadamard of traverse search.An improved algorithm based on cyclic shift method to construct the orthogonal coefficients is presented to construct a deterministic measurement matrix.Simulation results show that peak signal to noise ratio of the algorithm is higher than that of Gaussian random measurement matrix and Bernoulli random measurement matrix.

Key words: compression sensing, measurement matrix, coherence, cyclic shift, orthogonal coefficient, Hadamard matrix

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