A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging.

A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging.
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用于压缩单像素成像的哈达玛基础的俄罗斯娃娃排序

DOI:
10.1038/s41598-017-03725-6
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发表时间:
2017-06-14
期刊:
影响因子:
4.6
通讯作者:
Radwell N
Radwell N
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Sun MJ;Meng LT;Edgar MP;Padgett MJ;Radwell N

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单像素成像是一种替代成像技术,特别适合于成像模式,如超光谱成像、深度映射、3D剖面。然而,单像素技术需要连续测量,从而在空间分辨率和采集时间之间进行权衡,将实时视频应用限制在相对较低的分辨率。压缩感知技术可以用来改善这种权衡。然而,在这种低分辨率情况下,由于数据集缺乏稀疏性,传统压缩感知技术的影响有限。在这里,我们提出了一种替代的压缩感知方法,其中我们优化了Hadamard基的测量顺序,使得在离散增量下我们获得了不同空间分辨率的完整采样。此外,该方法采用确定性采集,而不是传统压缩感知中使用的随机采样。这种所谓的“俄罗斯娃娃”排序也受益于图像重建的最小计算开销。我们发现这种压缩方法与其他压缩感知技术一样表现良好,并且大大简化了后处理,从而大大加快了图像重建速度。因此,所提出的方法可用于低分辨率、高帧率或视频速率采集的单像素成像。
Single-pixel imaging is an alternate imaging technique particularly well-suited to imaging modalities such as hyper-spectral imaging, depth mapping, 3D profiling. However, the single-pixel technique requires sequential measurements resulting in a trade-off between spatial resolution and acquisition time, limiting real-time video applications to relatively low resolutions. Compressed sensing techniques can be used to improve this trade-off. However, in this low resolution regime, conventional compressed sensing techniques have limited impact due to lack of sparsity in the datasets. Here we present an alternative compressed sensing method in which we optimize the measurement order of the Hadamard basis, such that at discretized increments we obtain complete sampling for different spatial resolutions. In addition, this method uses deterministic acquisition, rather than the randomized sampling used in conventional compressed sensing. This so-called ‘Russian Dolls’ ordering also benefits from minimal computational overhead for image reconstruction. We find that this compressive approach performs as well as other compressive sensing techniques with greatly simplified post processing, resulting in significantly faster image reconstruction. Therefore, the proposed method may be useful for single-pixel imaging in the low resolution, high-frame rate regime, or video-rate acquisition.