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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
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: 725 | Views: 3,561

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), 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 95] [SCOPUS Times Cited 115]


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[CrossRef] [Full Text] [Web of Science Times Cited 27] [SCOPUS Times Cited 32]


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[9] J. Romberg, "Imaging via compressive sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 14-20, 2008.
[CrossRef] [Web of Science Times Cited 690] [SCOPUS Times Cited 877]


[10] T. Wan, N. Canagarajah, and A. Achim, "Compressive image fusion," IEEE International Conference on Image Processing, pp. 1308-1311, 2008.
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[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 40]


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[CrossRef] [SCOPUS Times Cited 43]


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[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 58]


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[CrossRef] [Web of Science Times Cited 2674] [SCOPUS Times Cited 3856]


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[CrossRef] [SCOPUS Times Cited 71]


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[CrossRef]




References Weight

Web of Science® Citations for all references: 46,545 TCR
SCOPUS® Citations for all references: 58,557 TCR

Web of Science® Average Citations per reference: 1,862 ACR
SCOPUS® Average Citations per reference: 2,342 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 2024-07-14 10:00 in 163 seconds.




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