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A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging
by
Padgett, Miles J.
, Sun, Ming-Jie
, Meng, Ling-Tong
, Radwell, Neal
, Edgar, Matthew P.
in
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
2017
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A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging
by
Padgett, Miles J.
, Sun, Ming-Jie
, Meng, Ling-Tong
, Radwell, Neal
, Edgar, Matthew P.
in
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
2017
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging
by
Padgett, Miles J.
, Sun, Ming-Jie
, Meng, Ling-Tong
, Radwell, Neal
, Edgar, Matthew P.
in
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
2017
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A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging
Journal Article
A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging
2017
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Overview
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.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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