Chinese Journal of Magnetic Resonance >
Comparison of Different Sampling Schemes in Compressed Sensing Reconstruction for DQ-SQ experiments
Received date: 2014-02-21
Revised date: 2014-10-27
Online published: 2014-12-05
Supported by
上海市科委资助项目(08DZ1900700).
To increase the speed of acquisition of two-dimensional solid-state DQ-SQ spectrum, a compressed sensing algorithm which makes use of the self-sparsity of the spectrum to construct under-sampled data. The energy function used in optimization is l1 norm together with the finite difference term. In the finite different term, we used different weights for the horizontal and vertical finite differences. Different sampling schemes were compared and pseudo-random sampling combined with compressed sensing reconstruction was found to yield the best results. Furthermore, we found that the extreme case of
pseudo-random sampling, that is, t1-cutoff sampling may be the best choice.the best results. Furthermore, we found that the extreme case of pseudo-random sampling, that is, t1-cutoff sampling may be the best choice.
Key words： solid-state NMR; compressed sensing; sampling scheme; DQ-SQ; pseudorandom
ZHENG Hui , HAN Ming-yue , HU Bing-wen* , YANG Guang* . Comparison of Different Sampling Schemes in Compressed Sensing Reconstruction for DQ-SQ experiments[J]. Chinese Journal of Magnetic Resonance, 2014 , 31(4) : 535 -547 . DOI: 10.11938/cjmr20140408
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