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. 2018 Jan 11;8:466. doi: 10.1038/s41598-017-18968-6

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Experimental comparison of different binary sampling methods. The results are reconstructed at the resolution of 256 × 256 from (a,f) a complete measurement, or (b–e,g–j) from a compressive measurement conducted at the compression rate of 6%. (b–d,g–i) have been obtained with a CS algorithm and (e,j) with the pseudoinverse. Sampling with: (b,g) randomly selected Walsh-Hadamard patterns; (c,h) randomly selected noiselet patterns; (d,e,i,j) Morlet wavelet-based random binary patterns.