An accelerated sparse time-invariant Radon transform in the mixed frequency-time domain based on iterative 2D model shrinkage
An accelerated sparse time-invariant Radon transform in the mixed frequency-time domain based on iterative 2D model shrinkage
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DOI：
10.1190/geo2012-0439.1
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发表时间：
2013-06
期刊：
影响因子：
3.3
通讯作者：
Wen-kai Lu
中科院分区：
文献类型：
--
作者：
Wen-kai Lu
摘要基于二维模型在时域的迭代收缩，提出了一种频时混合域的加速稀疏时不变Radon变换（RT）。我把它称为SRTIS。在传统的稀疏时不变RT在频-时混合域中，稀疏RT建模为稀疏逆问题，在时域中通过迭代重加权最小二乘（IRLS）算法来求解，并且在频域中实现正向和反向RT。在该方法中，IRLS被迭代2D模型收缩代替，即，Radon模型的稀疏性通过时域中的一些简单的2D模型收缩操作来提升。仿真和真实的数据解乘的例子使用抛物线RT的SRTIS相比，最小二乘RT，频域稀疏RT，和传统的时域稀疏RT在混合频率-时间域的更好的性能。
ABSTRACTI have developed an accelerated sparse time-invariant Radon transform (RT) in the mixed frequency-time domain based on iterative 2D model shrinkage in the time domain. I denote it as SRTIS. In the traditional sparse time-invariant RT in the mixed frequency-time domain, the sparse RT is modeled as a sparse inverse problem that is solved by the iteratively reweighted least-squares (IRLS) algorithm in the time domain, and the forward and inverse RTs are implemented in the frequency domain. In this method, IRLS is replaced by iterative 2D model shrinkage, i.e., the sparsity of the Radon model is promoted by some simple 2D model shrinkage operations in the time domain. Synthetic and real data demultiple examples using the parabolic RTs are given to demonstrate the better performance of the SRTIS when compared with the least-squares-based RT, the frequency domain sparse RT, and the traditional time-domain sparse RT in the mixed frequency-time domain.