...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Communications >Improvement of Compressive Sampling and Matching Pursuit Algorithm Based on Double Estimation
【24h】

Improvement of Compressive Sampling and Matching Pursuit Algorithm Based on Double Estimation

机译：基于双重估计的压缩采样匹配追踪算法的改进

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Compression sampling matching pursuit algorithm (CoSaMP) is widely applied to image reconstruction owing to its high precision of reconstruction, robustness, and simple operation. In this paper, we propose a new method, the CoSaMP based on double estimation, to properly overcome the shortcomings in CoSaMP for choosing too much optional atoms and imprecise choice. The concept of the maximum estimation, which is called maxValue , is proposed as a key point. The maxValue is calculated from the largest relevant 2k atoms of selected atoms in each iteration using least square solution method. At the next step, the maxValue is regard as a selection condition for the optional atoms to decrease the number of candidate atoms and increase its accuracy. The simulation results show that this algorithm can precisely reconstruct the original signal. Under the same sampling rate, compared to the CoSaMP, the proposed method can greatly improve the PSNR and reconstruction performance.
机译：压缩采样匹配追踪算法（CoSaMP）重构精度高，鲁棒性强，操作简单，因此被广泛应用于图像重构。在本文中，我们提出了一种新的方法，即基于双重估计的CoSaMP，以克服CoSaMP中选择过多的可选原子和选择不精确的缺点。提出了最大估计的概念，即maxValue，作为重点。使用最小二乘解法，在每次迭代中从选定原子的最大相关2k原子中计算出maxValue。在下一步中，将maxValue视为可选原子的选择条件，以减少候选原子的数量并提高其准确性。仿真结果表明，该算法可以精确地重建原始信号。在相同的采样率下，与CoSaMP相比，该方法可以大大提高PSNR和重建性能。

著录项

  • 来源
    《Journal of Communications》 |2016年第6期|573-578|共6页
  • 作者

    Guiling Sun; Yangyang Li; Haojie Yuan; Jingfei He; Tianyu Geng;

  • 作者单位

    College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China;

    College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China;

    College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China;

    College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China;

    College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Compressed sensing; double estimation; sparse reconstruction; atomic precision filter;

    机译：压缩感测;双重估计;稀疏重建原子精度过滤器;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号