摘要
压缩感知是针对稀疏或可压缩信号进行采样的同时即可对信号数据进行适当压缩的新理论,重建算法是其中关键的一部分,对采样过程中的准确性验证有着重要的意义。在研究和总结目前已有重建算法的基础上,提出了一种新的基于贪婪追踪的变步长自适应匹配追踪(VssAMP)算法。该算法通过可变步长及双重阈值控制重建精度,在信号稀疏度未知的前提下,即可对信号进行精确重建。实验结果表明,在相同条件下该算法的主客观重建效果均优于现有同类方法。
Compressive sensing（CS）is a novel signal sampling theory under the condition that the signal is sparse or compressible.It has the ability of compressing a signal during the process of sampling.Reconstruction algorithm is one of the key parts in compressive sensing,and it is of great significance to verify the sampling accuracy.In this paper,properties of the existing reconstruction algorithms are firstly analyzed.And then a new variable step size adaptive matching pursuit（VssAMP）algorithm based on greedy pursuit is presented by introducing an idea of variable step size.The proposed algorithm could control the accuracy of reconstruction by both variable step size and double thresholds although the sparsity of a signal is unknown.The experimental results show that the proposed algorithm can get better reconstruction performances and is superior to other algorithms both visually and objectively.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2010年第6期1639-1644,共6页
Acta Optica Sinica
基金
中央高校基本科研业务费专项基金(2009JBM022)资助课题
关键词
信号处理
重建算法
匹配追踪
压缩感知
稀疏表示
signal processing
reconstruction algorithm
matching pursuit
compressive sensing
sparse representation
