• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mathematical Problems in Engineering >Error in the Reconstruction of Nonsparse Images
【24h】

Error in the Reconstruction of Nonsparse Images

机译：非稀疏图像重建中的错误

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

Sparse signals, assuming a small number of nonzero coefficients in a transformation domain, can be reconstructed from a reduced set of measurements. In practical applications, signals are only approximately sparse. Images are a representative example of such approximately sparse signals in the two-dimensional (2D) discrete cosine transform (DCT) domain. Although a significant amount of image energy is well concentrated in a small number of transform coefficients, other nonzero coefficients appearing in the 2D-DCT domain make the images be only approximately sparse or nonsparse. In the compressive sensing theory, strict sparsity should be assumed. It means that the reconstruction algorithms will not be able to recover small valued coefficients (above the assumed sparsity) of nonsparse signals. In the literature, this kind of reconstruction error is described by appropriate error bound relations. In this paper, an exact relation for the expected reconstruction error is derived and presented in the form of a theorem. In addition to the theoretical proof, the presented theory is validated through numerical simulations.
机译：假设在变换域中有少量非零系数，则稀疏信号可以从一组减少的测量值中重建。在实际应用中，信号仅是稀疏的。图像是二维（2D）离散余弦变换（DCT）域中此类近似稀疏信号的代表示例。尽管大量的图像能量很好地集中在少量的变换系数中，但是出现在2D-DCT域中的其他非零系数使图像仅近似稀疏或稀疏。在压缩感测理论中，应假定严格的稀疏性。这意味着重构算法将无法恢复非稀疏信号的小值系数（高于假定的稀疏性）。在文献中，通过适当的错误边界关系来描述这种重建错误。在本文中，推导了预期重构误差的精确关系，并以定理的形式表示。除了理论证明，本文提出的理论还通过数值模拟得到了验证。

著录项

  • 来源
    《Mathematical Problems in Engineering》 |2018年第2期|4314527.1-4314527.10|共10页
  • 作者

    Brajovic Milos; Stankovic Isidora; Dakovic Milos; Ioana Cornel; Stankovic Ljubisa;

  • 作者单位

    Univ Montenegro, Fac Elect Engn, Podgorica 81000, Montenegro;

    Univ Montenegro, Fac Elect Engn, Podgorica 81000, Montenegro;

    Univ Montenegro, Fac Elect Engn, Podgorica 81000, Montenegro;

    Univ Grenoble Alpes, GIPSA Lab, INP, F-38400 St Martin Dheres, France;

    Univ Montenegro, Fac Elect Engn, Podgorica 81000, Montenegro;

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

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