计算机科学 ›› 2018, Vol. 45 ›› Issue (4): 306-311.doi: 10.11896/j.issn.1002-137X.2018.04.052

• 图形图像与模式识别 • 上一篇    下一篇

用于图像重构的基于行间支撑集相似度的CoSaMP算法

杜秀丽,顾斌斌,胡兴,邱少明,陈波   

  1. 大连大学信息工程学院辽宁省通信网络与信息处理重点实验室 辽宁 大连116622,大连大学信息工程学院辽宁省通信网络与信息处理重点实验室 辽宁 大连116622,大连大学信息工程学院辽宁省通信网络与信息处理重点实验室 辽宁 大连116622,大连大学信息工程学院辽宁省通信网络与信息处理重点实验室 辽宁 大连116622,大连大学信息工程学院辽宁省通信网络与信息处理重点实验室 辽宁 大连116622
  • 出版日期:2018-04-15 发布日期:2018-05-11
  • 基金资助:
    本文受辽宁省教育厅项目:高速眼图测试关键技术研究(L2014495)资助

Support Similarity between Lines Based CoSaMP Algorithm for Image Reconstruction

DU Xiu-li, GU Bin-bin, HU Xing, QIU Shao-ming and CHEN Bo   

  • Online:2018-04-15 Published:2018-05-11

摘要: 压缩采样匹配追踪(CoSaMP)算法的性能受初始支撑集选择的制约,初始支撑集选择不准确不仅影响重构精度,还会降低重构速度。针对该问题,将图像在稀疏域的结构特性引入到CoSaMP算法中,提出了支撑集相似度的概念;利用数字图像相邻行之间原子支撑集的相似性,提出了基于行间支撑集相似度的CoSaMP算法。实验结果表明,在同等采样率的条件下, 与传统的CoSaMP算法相比,所提算法在不增加算法时间复杂度的同时提高了重构质量 ,峰值信噪比提高了0.6~2.5dB。

关键词: 压缩感知,贪婪算法,压缩采样匹配追踪(CoSaMP),稀疏支撑集,相似度

Abstract: The performance of compressive sampling matching pursuit(CoSaMP) is restricted to the choice of its initial support set. Choosing initial support set inaccurately will not only affect the accuracy of recons itution,but also reduce the speed of reconstruction.In order to solve this problem,the stucture of image in sparse domain was introduced into CoSaMP algorithm,and the concept of support set similarity was presented.Then CoSaMP algorithm based on support similarity between lines was proposed and the high similarity between the adjoining rows in one digital image was used.The results of this experiment show that the proposed algorithm has higher quality in reconstruction without increa-sing the time complexity of algorithm,and the peak signal-to-noise ratio enhances 0.6~2.5dB compared with the traditional CoSaMP algorithm under the same condition of sampling frequency.

Key words: Compressive sensing,Greedy algorithm,Compressive sampling matching pursuit,Sparse support,Similarity

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