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International Journal for Multiscale Computational Engineering

Publication de 6  numéros par an

ISSN Imprimer: 1543-1649

ISSN En ligne: 1940-4352

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.4 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 2.2 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00034 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.46 SJR: 0.333 SNIP: 0.606 CiteScore™:: 3.1 H-Index: 31

Indexed in

Energy-Based Fusion Scheme for Surveillance and Navigation

Volume 8, Numéro 6, 2010, pp. 631-640
DOI: 10.1615/IntJMultCompEng.v8.i6.60
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RÉSUMÉ

Image fusion is used to integrate multiple images into a composite image which contains complementary information from each of the source images. In defense applications, fusion is widely employed to obtain images pertaining to the object under surveillance and also for mapping terrain for navigation purposes. Although there are a many fusion algorithms reported in the literature, the need is for a computationally efficient fusion rule that can be implemented easily in hardware. Driven by this motivation we have formulated a discrete wavelet transform{based fusion technique that uses the energy of the wavelet coefficients to determine the fusion weights for the approximate image and choose maximum intensity rule for the detail image. Surveillance imaging generally uses two imaging sources, one an infrared camera and the other a conventional digital camera, and the images are usually captured under low lighting and night-time conditions. We used the structural similarity index, mutual information, and standard deviation as metrics to evaluate the performance of our fusion scheme with existing algorithms. Our experiments have shown that the algorithm developed produces good results under the constraints imposed by this application.

RÉFÉRENCES
  1. Burt, P. J. and Adelson, E. H., The Laplacian pyramid as a compact image code. DOI: 10.1109/TCOM.1983.1095851

  2. Burt, P. J., The pyramid as a structure for efficient computation. DOI: 10.1007/978-3-642-51590-3_2

  3. Das, S., Zhang, Y.-L., and Krebs, W. K., Color night vision for navigation and surveillance. DOI: 10.3141/1708-05

  4. Canga, E. F., Nikolov, S. G., Canagarajah, C. N., Bull, D. R., Dixon, T. D., Noyes, J. M., and Troscianko, T., Characterization of image fusion quality metrics for surveillance applications over band-limited channels. DOI: 10.1109/ICIF.2005.1591894

  5. Chen, Y. and Blum, R. S., Experimental tests of image fusion for night vision. DOI: 10.1109/ICIF.2005.1591895

  6. Image Fusion, <a href="http://www.imagefusion.org">www.imagefusion.org</a>.

  7. Kim, M. G., Dinstein, I., and Shaw, L., A prototype filter design approach to pyramid generation. DOI: 10.1109/34.250842

  8. Maruthi, R. and Suresh, R. M., Metrics for measuring the quality of fused images. DOI: 10.1109/ICCIMA.2007.44

  9. Qu, G., Zhang, D., and Yan, P., Information measure for performance of image fusion. DOI: 10.1049/el:20020212

  10. Toet, A., Image fusion by a ratio of low pass pyramid. DOI: 10.1016/0167-8655(89)90003-2

  11. Toet, A., van Ruvven, L. J., and Valeton, J. M., Merging thermal and visual images by a contrast pyramid. DOI: 10.1117/12.7977034

  12. Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P., Image quality assessment: From error visibility to structural similarity. DOI: 10.1109/TIP.2003.819861

  13. Zhang, Z. and Blum, R. S., A categorization of multiscaledecomposition-based image fusion schemes with a performance study for a digital camera application. DOI: 10.1109/5.775414

  14. Zheng, Y., Hou, X., Bian, T., and Oin, Z., Effective image fusion rules of multiscale image decomposition. DOI: 10.1109/ISPA.2007.4383720

CITÉ PAR
  1. Sadhasivam Senthilkumar, Gnanasivam P., Effect of noise on wavelet transform based image fusion algorithms, 2015 Global Conference on Communication Technologies (GCCT), 2015. Crossref

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