A Compression Sensing Sampling Scheme Based on the Golden Section Principle

Xiao Ning Li; Zhang Hong Wu; Hao Yang Xing

doi:10.4028/www.scientific.net/AMM.644-650.4567

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650A Compression Sensing Sampling Scheme Based on the...

A Compression Sensing Sampling Scheme Based on the Golden Section Principle

Abstract:

In classic radial sampling scheme, angle intervals between adjacent straight sampling lines are the same. And so the coherence between the sampling matrix and the sparse matrix is high. Many pseudo-shadows will occur on the reconstructed image. For this problem, we put forward a novel sampling scheme in which the scan lines are placed in the manner of golden section angle interval. In the resulting sampling matrix, the scan lines scatter randomly on the whole. Experimental results demonstrate that the algorithm proposed in this paper has lower correlation coefficient between sampling matrix and sparse matrix than classic radial sampling scheme and random radial sampling scheme. Image can be accurately reconstructed by collecting less data than the other two schemes.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

4567-4572

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.4567

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Online since:

September 2014

Authors:

Xiao Ning Li*, Zhang Hong Wu, Hao Yang Xing

Keywords:

Compressive Sensing, Golden Section, Image Reconstruction, Radial Sampling, Sampling Matrix

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* - Corresponding Author

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