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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 644266260
doi: 10.4316/AECE


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  4/2013 - 14

Combined Sparsifying Transforms for Compressive Image Fusion

WU, C. See more information about WU, C. on SCOPUS See more information about WU, C. on IEEExplore See more information about WU, C. on Web of Science, WANG, H. See more information about  WANG, H. on SCOPUS See more information about  WANG, H. on SCOPUS See more information about WANG, H. on Web of Science, XU, X. See more information about  XU, X. on SCOPUS See more information about  XU, X. on SCOPUS See more information about XU, X. on Web of Science, ZHAO, L. See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on Web of Science
 
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Download PDF pdficon (821 KB) | Citation | Downloads: 262 | Views: 1,451

Author keywords
compressive sensing, combined sparsifying transforms, image fusion

References keywords
processing(14), image(13), sensing(11), signal(8), fusion(8), sparse(6), information(5), zhang(4), imaging(4), icip(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 79 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04014
Web of Science Accession Number: 000331461300014
SCOPUS ID: 84890250999

Abstract
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In this paper, we present a new compressive image fusion method based on combined sparsifying transforms. First, the framework of compressive image fusion is introduced briefly. Then, combined sparsifying transforms are presented to enhance the sparsity of images. Finally, a reconstruction algorithm based on the nonlinear conjugate gradient is presented to get the fused image. The simulations demonstrate that by using the combined sparsifying transforms better results can be achieved in terms of both the subjective visual effect and the objective evaluation indexes than using only a single sparsifying transform for compressive image fusion.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 20]


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[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 54]


[7] M. Fira, L. Goras, C. Barabasa, and N. Cleju, "On ECG Compressed Sensing using Specific Overcomplete Dictionaries," Advances in Electrical and Computer Engineering, vol. 10, no. 4, pp. 23-28, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 12] [SCOPUS Times Cited 17]


[8] M. Fira, L. Goras, "A New Method for EEG Compressive Sensing," Advances in Electrical and Computer Engineering, vol. 12, no. 4, pp. 71-76, 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]


[9] J. Romberg, "Imaging via compressive sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 14-20, 2008.
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[10] T. Wan, N. Canagarajah, and A. Achim, "Compressive image fusion," IEEE International Conference on Image Processing, pp. 1308-1311, 2008.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 40]


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[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 27]


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[CrossRef] [SCOPUS Times Cited 25]


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[CrossRef] [Web of Science Times Cited 24] [SCOPUS Times Cited 31]


[15] M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, "Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems," IEEE Journal of Selected Topics in Signal Processing, vol. 1, no. 4, pp. 586-597, 2007.
[CrossRef] [Web of Science Times Cited 1043] [SCOPUS Times Cited 1523]


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[CrossRef] [Web of Science Times Cited 1331] [SCOPUS Times Cited 2336]


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[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 73]


[18] Q. Zhang, B. L. Guo, "Multifocus image fusion using the nonsubsampled contourlet transform," Signal Processing, vol. 89, no. 7, pp. 1334-1346, 2009.
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[22] G. H. Qu, D. L. Zhang, and P. F. Yan, "Information measure for performance of image fusion," Electronics Letters, vol. 38, no. 7, pp. 313-315, 2002.
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[CrossRef]




References Weight

Web of Science® Citations for all references: 19,780 TCR
SCOPUS® Citations for all references: 27,779 TCR

Web of Science® Average Citations per reference: 791 ACR
SCOPUS® Average Citations per reference: 1,111 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2016-12-03 10:21 in 137 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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