508
Views
21
CrossRef citations to date
0
Altmetric
Articles

Novel fusion method for SAR and optical images based on non-subsampled shearlet transform

, , &
Pages 4590-4604 | Received 22 May 2019, Accepted 12 Dec 2019, Published online: 20 Feb 2020

References

  • Ban, Y., H. Hu, and I. M. Rangel. 2010. “Fusion of Quickbird MS and RADARSAT SAR Data for Urban Land-Cover Mapping: Object-Based and Knowledge-Based Approach.” International Journal of Remote Sensing 31 (6): 1391–1410. doi:10.1080/01431160903475415.
  • Ban, Y., H. Hu, and I. Rangel. 2007. “Fusion of RADARSAT Fine-Beam SAR and QuickBird Data for Land-Cover Mapping and Change Detection.” In, edited by W. Ju and S. Zhao, 67522H. doi:10.1117/12.760747.
  • Bhatnagar, G., Q. M. J. Wu, and Z. Liu. 2013. “Human Visual System Inspired Multi-Modal Medical Image Fusion Framework.” Expert Systems with Applications 40 (5): 1708–1720. doi:10.1016/j.eswa.2012.09.011.
  • Borghys, D., M. Shimoni, and C. Perneel. 2007. “Change Detection in Urban Scenes by Fusion of SAR and Hyperspectral Data.” In edited by M. Ehlers and U. Michel, 67490R. doi:10.1117/12.738767.
  • Brekke, C., and A. H. S. Solberg. 2005. “Oil Spill Detection by Satellite Remote Sensing.” Remote Sensing of Environment 95: 1–13. doi:10.1016/j.rse.2004.11.015.
  • Cheng, B., L. Jin, and G. Li. 2018. “Infrared and Visual Image Fusion Using LNSST and an Adaptive Dual-Channel PCNN with Triple-Linking Strength.” Neurocomputing 310 (October): 135–147. doi:10.1016/j.neucom.2018.05.028.
  • Da Cunha, A.L., J. Zhou and M. N. Do. 2006. “The Nonsubsampled Contourlet Transform: Theory, Design, and Applications.” IEEE Transactions on Image Processing 15 (10): 3089–3101. doi:10.1109/TIP.2006.877507.
  • Do, M. N., and M. Vetterli. 2005. “The Contourlet Transform: An Efficient Directional Multiresolution Image Representation.” IEEE Transactions on Image Processing 14 (12): 2091–2106. doi:10.1109/TIP.2005.859376.
  • Easley, G., D. Labate, and W.-Q. Lim. 2008. “Sparse Directional Image Representations Using the Discrete Shearlet Transform.” Applied and Computational Harmonic Analysis 25 (1): 25–46. doi:10.1016/j.acha.2007.09.003.
  • Errico, A., C. V. Angelino, L. Cicala, G. Persechino, C. Ferrara, M. Lega, A. Vallario, et al. 2015. “Detection of Environmental Hazards through the Feature-Based Fusion of Optical and SAR Data: A Case Study in Southern Italy.” International Journal of Remote Sensing 36 (13): 3345–3367. doi:10.1080/01431161.2015.1054960.
  • Ghahremani, M., and H. Ghassemian. 2015. “Remote-Sensing Image Fusion Based on Curvelets and ICA.” International Journal of Remote Sensing 36 (16): 4131–4143. doi:10.1080/01431161.2015.1071897.
  • Goodman, J. W. 1976. “Some Fundamental Properties of Speckle.” Journal of the Optical Society of America 66 (11): 1145. The Optical Society . doi:10.1364/josa.66.001145.
  • Haghighat, M. B. A., A. Aghagolzadeh, and H. Seyedarabi. 2011. “Multi-Focus Image Fusion for Visual Sensor Networks in DCT Domain.” Computers and Electrical Engineering 37 (5): 789–797. doi:10.1016/j.compeleceng.2011.04.016.
  • Huang, Y., D. Bi, and D. Wu. 2018. “Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain.” Sensors 18 (4): 1169. doi:10.3390/s18041169.
  • Joshi, N., M. Baumann, A. Ehammer, R. Fensholt, K. Grogan, P. Hostert, M. Jepsen, et al. 2016. “A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring.” Remote Sensing 8 (1): 70. doi:10.3390/rs8010070.
  • Kim, S., W.-J. Song, and S.-H. Kim. 2018. “Double Weight-Based SAR and Infrared Sensor Fusion for Automatic Ground Target Recognition with Deep Learning.” Remote Sensing 10 (2): 72. doi:10.3390/rs10010072.
  • Kong, W., L. Zhang, and Y. Lei. 2014. “Novel Fusion Method for Visible Light and Infrared Images Based on NSST-SF-PCNN.” Infrared Physics and Technology 65: 103–112. Elsevier. doi:10.1016/j.infrared.2014.04.003.
  • Li, Q., X. Yang, W. Wei, K. Liu, and G. Jeon. 2018. “Multi-Focus Image Fusion Method for Vision Sensor Systems via Dictionary Learning with Guided Filter.” Sensors 18 (7): 2143. doi:10.3390/s18072143.
  • Li, W., X. Hu, J. Du, and B. Xiao. 2017. “Adaptive Remote-Sensing Image Fusion Based on Dynamic Gradient Sparse and Average Gradient Difference.” International Journal of Remote Sensing 38 (23): 7316–7332. doi:10.1080/01431161.2017.1371863.
  • Sheng, J., X. Yang, and Z. Dong. 2018. “Fusion of SAR and Visible Images Based on NSST-IHS and Sparse Representation.” Journal of Graphics 39 (2): 201–208. doi:10.11996/JG.j.2095-302X.2018020201.
  • Singh, S., R. S. A. Deep Gupta, and V. Kumar. 2015. “Nonsubsampled Shearlet Based CT and MR Medical Image Fusion Using Biologically Inspired Spiking Neural Network.” Biomedical Signal Processing and Control 18: 91–101. Elsevier Ltd. doi:10.1016/j.bspc.2014.11.009.
  • Stȩpniak, C. 2011. “Coefficient of Variation.” In International Encyclopedia of Statistical Science, 267. Berlin Heidelberg: Springer. doi:10.1007/978-3-642-04898-2_177.
  • Tang, Z., J. Wang, and S. Huang. 2000. “Wavelet Transform Application for Image Fusion.” In edited by H. H. Szu, M. Vetterli, W. J. Campbell, and J. R. Buss, 462–469. doi:10.1117/12.381706.
  • Wang, H., and C. Glennie. 2015. “Fusion of Waveform LiDAR Data and Hyperspectral Imagery for Land Cover Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 108 (October): 1–11. Elsevier B.V. . doi:10.1016/j.isprsjprs.2015.05.012.
  • Wang, J., J. Peng, X. Jiang, X. Feng, and J. Zhou. 2017. “Remote-Sensing Image Fusion Using Sparse Representation with Sub-Dictionaries.” International Journal of Remote Sensing 38 (12): 3564–3585. doi:10.1080/01431161.2017.1302106.
  • Yi, W., Y. Zeng, and Z. Yuan. 2018. “Fusion of GF-3 SAR and Optical Images Based on the Nonsubsampled Contourlet Transform.” Acta Optica Sinica 38 (11): 1110002. Chinese Optical Society . doi:10.3788/AOS201838.1110002.
  • Zhang, L., and J. Zhang. 2018. “A Novel Remote-Sensing Image Fusion Method Based on Hybrid Visual Saliency Analysis.” International Journal of Remote Sensing 39 (22): 7942–7964. doi:10.1080/01431161.2018.1479791.
  • Zhang, X., J. Ren, Z. Huang, and F. Zhu. 2016. “Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.” Sensors 16 (9): 1503. doi:10.3390/s16091503.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.