[1]陈少利,杨敏. 改进变步长快速迭代收缩阈值算法[J].计算机技术与发展,2017,27(10):69-73.
　CHEN Shao-li,YANG Min. An Improved Fast Iterative Shrinkage-thresholding Algorithm with Variable Stepsize[J].,2017,27(10):69-73.
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 改进变步长快速迭代收缩阈值算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年10期
页码:
69-73
栏目:
智能、算法、系统工程
出版日期:
2017-10-10

文章信息/Info

Title:
 An Improved Fast Iterative Shrinkage-thresholding Algorithm with Variable Stepsize
文章编号:
1673-629X（2017)10-0069-05
作者:
 陈少利; 杨敏
 南京邮电大学 自动化学院
Author(s):
 CHEN Shao-li; YANG Min
关键词:
 ; 快速迭代收缩阈值算法; Barzilai-Borwein算子; 全变分模型; 压缩感知; 图像去噪
Keywords:
 ; fast iterative shrinkage-threshold algorithm; Barzilai-Borwein operator; total variation model; compressed sensing; image de-nosing
分类号:
TP391
文献标志码:
A
摘要:
 图像复原问题是图像处理中的一项重要研究内容,解决图像复原问题,往往涉及到大量的数据集和未知信息.为了解决此类高维数据优化问题,前向后向算法提供了简洁、实用的方法.快速迭代收缩阈值算法是在前向后向算法的基础上加入了全局加速算子,一定程度上提高了算法的收敛速率.但是,快速迭代收缩阈值算法在解决最小值优化问题时,采用的是固定步长因子,限制了算法的收敛速率.针对该问题,结合Barzilai-Borwein算子提出一种改进的变步长算法.改进算法在每次迭代中利用前两步的迭代信息更新步长因子,加快了算法的收敛.将该算法应用于压缩感知和图像去噪中,数值实验结果表明:该算法改进了原算法的收敛速率.因此,改进变步长快速迭代收缩阈值算法不仅提高了算法的效率,同时提高了信号复原的信噪比.
Abstract:
 Image restoration is an important research in image processing and solving of it involves large databases and many unknowns. The forward-backward splitting method provides a simple,practicable solution to solve the kinds of data optimization with high dimen-sion. The fast iterative shrinkage-thresholding algorithm joins the global acceleration operator and improve its convergence rate based on the forward-backward algorithm. However,the fixed step-size limits its speed of the convergence in minimal optimization solving. To ad-dress that,an improved algorithm with variable stepsize by using Barzilai-Borwein ( BB) operator is proposed which updates the step size with the iterative information of the first two steps in each iteration to accelerate its convergence. Then it’ s applied to image denosing and compressed sensing. The experimental results demonstrate that it is more efficient than the original fast iterative shrinkage-threshold algo-rithm,not only in the efficiency but also in the signal to noise ratio of signal restoration.

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更新日期/Last Update: 2017-11-23