Optimized projections for compressed sensing
Optimized projections for compressed sensing
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DOI：
10.1109/tsp.2007.900760
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发表时间：
2007-12-01
影响因子：
5.4
通讯作者：
Elad, Michael
中科院分区：
文献类型：
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作者：
Elad, Michael
压缩感知（CS）提供了一个联合的压缩和传感过程，基于处理信号的稀疏表示的存在，和一组投影测量。到目前为止，关于CS的工作通常假设投影是随机绘制的。在本文中，我们考虑这些预测的优化。由于这样的直接优化是禁止的，我们的目标是有效字典的相互一致性的平均测量，并证明这会导致更好的CS重建性能。的基础追求（BP）和正交匹配追求（OMP）示出受益于新设计的投影，与减少的错误率的一个因素的10倍及以上。
Compressed sensing (CS) offers a joint compression and sensing processes, based on the existence of a sparse representation of the treated signal,and a set of projected measurements. Work on CS thus far typically assumes that the projections are drawn at random. In this paper, we consider the optimization of these projections. Since such a direct optimization is prohibitive, we target an average measure of the mutual coherence of the effective dictionary, and demonstrate that this leads to better CS reconstruction performance. Both the basis pursuit (BP) and the orthogonal matching pursuit (OMP) are shown to benefit from the newly designed projections, with a reduction of the error rate by a factor of 10 and beyond.