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

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...

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Bibliographic Details
Published in:Scientific reports Vol. 7; no. 1; pp. 3464 - 7
Main Authors: Sun, Ming-Jie, Meng, Ling-Tong, Edgar, Matthew P., Padgett, Miles J., Radwell, Neal
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 14.06.2017
Nature Publishing Group
Nature Portfolio
Subjects:
639/624/1075/146
639/624/1107/510
Computer applications
Humanities and Social Sciences
Image processing
multidisciplinary
Sampling
Science
Science (multidisciplinary)
Sensors
Sparsity
Spatial discrimination
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary: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.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-03725-6