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Next issue: Feb 2018
Avg review time: 105 days


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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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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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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
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (821 KB) | Citation | Downloads: 293 | Views: 1,702

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

[1] E. J. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Transactions on Information Theory, vol. 52, no. 2, pp. 489-509, 2006.
[CrossRef] [Web of Science Times Cited 6505] [SCOPUS Times Cited 8401]


[2] D. L. Donoho, "Compressed Sensing," IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, 2006.
[CrossRef] [Web of Science Times Cited 10160] [SCOPUS Times Cited 13463]


[3] M. B. Wakin, J. N. Laska, M. F. Duarte, et al. "An architecture for compressive imaging," IEEE International Conference on Image Processing, pp.1273-1276, 2006.
[CrossRef] [Web of Science Times Cited 106] [SCOPUS Times Cited 194]


[4] M. F. Duarte, M. A. Davenport, D. Takhar, et al. "Single-pixel imaging via compressive sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 83-91, 2008.
[CrossRef] [SCOPUS Times Cited 1341]


[5] D. Giacobello, M. G. Christensen, M. N. Murthi, S. H. Jensen, and M. Moonen, "Retrieving Sparse Patterns Using a Compressed Sensing Framework: Applications to Speech Coding Based on Sparse Linear Prediction," IEEE Signal Processing Letters, vol. 17, no. 1, pp. 103-106, 2010.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 52]


[6] D. Giacobello, M. G. Christensen, M. N. Murthi, S. H. Jensen, and M. Moonen, "Sparse linear prediction and its applications to speech processing," IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, no. 5, pp. 1644-1657, 2012.
[CrossRef] [Web of Science Times Cited 50] [SCOPUS Times Cited 67]


[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 16] [SCOPUS Times Cited 19]


[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.
[CrossRef] [SCOPUS Times Cited 587]


[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 25] [SCOPUS Times Cited 64]


[11] T. Wan, Z. C. Qin, "An application of compressive sensing for image fusion," International Journal of Computer Mathematics, vol. 88, no. 18, pp. 3915-3930, 2011.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 30]


[12] X. Li, S. Y. Qin, "Efficient fusion for infrared and visible images based on compressive sensing principle," IET Image Processing, vol. 5, no. 2, pp. 141-147, 2011.
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 60]


[13] X. Y. Luo, J. Zhang, J. Y. Yang, and Q. H. Dai, "Image fusion in compressed sensing," IEEE International Conference on Image Processing, pp. 2205-2208, 2009.
[CrossRef] [SCOPUS Times Cited 34]


[14] X. Qu, X. Cao, D. Guo, C. Hu, and Z. Chen, "Combined sparsifying transforms for compressed sensing MRI," Electronics Letters, vol. 46, no. 2, pp. 121-123, 2010.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 34]


[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 1277] [SCOPUS Times Cited 1789]


[16] M. N. Do, M. Vetterli, "The contourlet transform: an efficient directional multiresolution image representation," IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 1629-1632, 2005.
[CrossRef] [Web of Science Times Cited 1565] [SCOPUS Times Cited 2719]


[17] Y. Lu, M. N. Do, "A new contourlet transform with sharp frequency localization," IEEE International Conference on Image Processing, pp. 1629-1632, 2006.
[CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 133]


[18] Q. Zhang, B. L. Guo, "Multifocus image fusion using the nonsubsampled contourlet transform," Signal Processing, vol. 89, no. 7, pp. 1334-1346, 2009.
[CrossRef] [Web of Science Times Cited 196] [SCOPUS Times Cited 265]


[19] M. Lustig, D. Donoho, and J. M. Pauly, "Sparse MRI: the application of compressed sensing for rapid MR Imaging," Magnetic Resonance in Medicines, vol. 58, no. 10, pp. 1182-1195, 2007.
[CrossRef] [Web of Science Times Cited 2226] [SCOPUS Times Cited 2499]


[20] M. Lustig, D. L. Donoho, J. M. Santos, and J. M. Pauly, "Compressed sensing MRI," IEEE Signal Magazine, vol. 25, no. 2, pp. 72-82, 2008.
[CrossRef] [SCOPUS Times Cited 646]


[21] W. W. Hager, H. Zhang. "A survey of nonlinear conjugate gradient methods," Pacific journal of Optimization, vol. 2, no. 1, pp. 35-58, 2006.

[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.
[CrossRef] [Web of Science Times Cited 399] [SCOPUS Times Cited 589]


[23] V. Petrovic, C. Xydeas, "On the effects of sensor noise in pixel-level image fusion performance," Proceedings of the Third International Conference on Information Fusion, vol. 2, pp. 14-19, 2010.
[CrossRef] [SCOPUS Times Cited 57]


[24] M. Aharon, M. Elad, and A. Bruckstein, "K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation," IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4311-4322, 2006.
[CrossRef]




References Weight

Web of Science® Citations for all references: 22,693 TCR
SCOPUS® Citations for all references: 33,046 TCR

Web of Science® Average Citations per reference: 908 ACR
SCOPUS® Average Citations per reference: 1,322 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 2017-12-13 11:59 in 145 seconds.




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


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