[1] Liao Fan, Yan Lu, Wu Jiasong, Han Xu, et al. Algorithm for reconstructing compressed sensing color imagingusing the quaternion total variation [J]. Journal of Southeast University (English Edition), 2015, 31 (1): 51-54. [doi:10.3969/j.issn.1003-7985.2015.01.009]

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Algorithm for reconstructing compressed sensing color imagingusing the quaternion total variation()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

31

Issue:

2015 1

Page:

51-54

Research Field:

Computer Science and Engineering

Publishing date:

2015-03-30

Info

Title:

Algorithm for reconstructing compressed sensing color imagingusing the quaternion total variation

Author(s):

Liao Fan¹;  Yan Lu¹;  Wu Jiasong¹;  2;  Han Xu¹;  Shu Huazhong¹;  2

¹Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China
²Centre de Recherche en Information Médicale Sino-français(CRIBs), Southeast University, Nanjing 210096, China

Keywords:

total variation;  compressed sensing;  quaternion;  sparse reconstruction;  color image restoration

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2015.01.009

Abstract:

A new method for reconstructing the compressed sensing color image by solving an optimization problem based on total variation in the quaternion field is proposed, which can effectively improve the reconstructing ability of the color image. First, the color image is converted from RGB(red, green, blue)space to CMYK(cyan, magenta, yellow, black)space, which is assigned to a quaternion matrix. Meanwhile, the quaternion matrix is converted into the information of the phase and amplitude by the Euler form of the quaternion. Secondly, the phase and amplitude of the quaternion matrix are used as the smoothness constraints for the compressed sensing(CS)problem to make the reconstructing results more accurate. Finally, an iterative method based on gradient is used to solve the CS problem. Experimental results show that by considering the information of the phase and amplitude, the proposed method can achieve better performance than the existing method that treats the three components of the color image as independent parts.

References:

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[11] Oliveri G, Anselmi N, Massa A. Compressive sensing imaging of non-sparse 2D scatterers by a total-variation approach within the born approximation[J]. IEEE Transactions on Antennas and Propagation, 2014, 62(10): 5157-5170.

Memo

Memo:

Biographies: Liao Fan(1983—), male, graduate; Shu Huazhong(corresponding author), male, doctor, professor, shu.list@seu.edu.cn.
Foundation items: The National Basic Research Program of China(973 Program)(No.2011CB707904), the National Natural Science Foundation of China(No.61201344, 61271312, 61073138), the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092110023, 20120092120036), the Natural Science Foundation of Jiangsu Province(No.BK2012329).
Citation: Liao Fan, Yan Lu, Wu Jiasong, et al. Algorithm for reconstructing compressed sensing color imaging using the quaternion total variation[J].Journal of Southeast University(English Edition), 2015, 31(1):51-54.[doi:10.3969/j.issn.1003-7985.2015.01.009]

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