36
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Novel fusion strategy for image fusion using rescue hunt optimization-based modified guidance model

, , &
Pages 129-153 | Received 16 Sep 2023, Accepted 10 Mar 2024, Published online: 21 Mar 2024

References

  • Abdipour, M. and Nooshyar, M., 2016. Multi-focus image fusion using sharpness criteria for visual sensor networks in wavelet domain. Computers & Electrical Engineering, 51, 74–88. doi:10.1016/j.compeleceng.2016.03.011.
  • Adelson, E.H., et al., 1984. Pyramid methods in image processing. RCA Engineer, 29 (6), 33–41.
  • Arliani, G.G., et al., 2011. The Brazilian Football Association (CBF) model for epidemiological studies on professional soccer player injuries. Clinics, 66 (10), 1707–1712. doi:10.1590/S1807-59322011001000007.
  • Aymaz, S., Köse, C., and Aymaz, Ş., 2020. Multi-focus image fusion for different datasets with super-resolution using gradient-based new fusion rule. Multimedia Tools and Applications, 79 (19–20), 13311–13350. doi:10.1007/s11042-020-08670-7
  • Bavirisetti, D.P. and Dhuli, R., 2015. Multi sensor image fusion using saliency map detection. International Review on Computers and Software (IRECOS), 10 (7), 757–763. doi:10.15866/irecos.v10i7.6793.
  • Bavirisetti, D.P. and Dhuli, R., 2016. Two-scale image fusion of visible and infrared images using saliency detection. Infrared Physics and Technology, 76, 52–64. doi:10.1016/j.infrared.2016.01.009
  • Ben Hamza, A., et al., 2005. A multiscale approach to pixel-level image fusion. Integrated Computer-Aided Engineering, 12 (2), 135–146. doi:10.3233/ICA-2005-12201.
  • Bhatnagar, G., Wu, Q.J., and Liu, Z., 2013. Directive contrast based multimodal medical image fusion in NSCT domain. IEEE Transactions on Multimedia, 15 (5), 1014–1024. doi:10.1109/TMM.2013.2244870.
  • Bhavana, D., Kishore Kumar, K., and Ravi Tej, D., 2020. Infrared and visible image fusion using the latent low-rank technique for surveillance applications. International Journal of Speech Technology, 25 (3), 551–560. doi:10.1007/s10772-021-09822-2.
  • Bhavana, D., Kishore Kumar, K., and Ravi Tej, D., 2021. Infrared and visible image fusion using latent low rank technique for surveillance applications. International Journal of Speech Technology, 25 (3), 1–10. doi:10.1007/s10772-021-09822-2.
  • Blum, R.S. and Liu, Z., 2018. Multi-sensor image fusion and its applications. Boca Raton: CRC press.
  • Borwonwatanadelok, P., Rattanapitak, W., and Udomhunsakul, S., 2009. Multi-focus image fusion based on stationary wavelet transform and extended spatial frequency measurement. In 2009 international conference on electronic computer technology, Macau, China, IEEE, 77–81.
  • Candes, E., et al., 2006. Fast discrete curvelet transforms. Multiscale Modeling and Simulation, 5 (3), 861–899. doi:10.1137/05064182X.
  • Dogra, A., et al., 2020. An efficient image integration algorithm for night mode vision applications. Multimedia Tools and Applications, 79 (15–16), 10995–11012. doi:10.1007/s11042-018-6631-z.
  • Gao, C., et al., 2021. Infrared and visible image fusion method based on ResNet in a nonsubsampled contourlet transform domain. IEEE Access, 9, 91883–91895. doi:10.1109/ACCESS.2021.3086096.
  • Gattim, N.K., et al., 2017. Multimodal image fusion using curvelet and genetic algorithm. Journal of Scientific & Industrial Research, 76, 694–696.
  • Ineneji, C. and Kusaf, M., 2019. Hybrid weapon detection algorithm, using material test and fuzzy logic system. Computers & Electrical Engineering, 78, 437–448. doi:10.1016/j.compeleceng.2019.08.005.
  • Jha, A., Bose, S., and Banerjee, B., 2023. GAF-Net: improving the performance of remote sensing image fusion using novel global self and cross attention learning. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, USA, 6354–6363.
  • Jin, X., et al., 2017. A survey of infrared and visual image fusion methods. Infrared Physics & Technology, 85, 478–501. doi:10.1016/j.infrared.2017.07.010.
  • Khajwal, A.B., Cheng, C.S., and Noshadravan, A., 2023. Post‐disaster damage classification based on deep multi‐view image fusion. Computer-Aided Civil and Infrastructure Engineering, 38 (4), 528–544. doi:10.1111/mice.12890.
  • Khaleghi, B., et al., 2013. Multisensor data fusion: a review of the state-of-the-art. Information Fusion, 14 (1), 28–44. doi:10.1016/j.inffus.2011.08.001.
  • Lei, X., Pan, H., and Huang, X., 2019. A dilated CNN model for image classification. IEEE Access, 7, 124087–124095. doi:10.1109/ACCESS.2019.2927169.
  • Li, S., et al., 2017. Pixel-level image fusion: a survey of the state of the art. Information Fusion, 33, 100–112. doi:10.1016/j.inffus.2016.05.004.
  • LLVIP dataset. 2023. Available from: https://drive.google.com/file/d/1VTlT3Y7e1h-Zsne4zahjx5q0TK2ClMVv/view?usp=sharingaccessed [ Accessed September 2023].
  • Meher, B., et al., 2022. Visible and infrared image fusion using an efficient adaptive transition region extraction technique. Engineering Science and Technology, an International Journal, 29, 101037. doi:10.1016/j.jestch.2021.06.017.
  • Mirjalili, S., Mirjalili, S.M., and Lewis, A., 2014. Grey wolf optimizer. Advances in Engineering Software, 69, 46–61. doi:10.1016/j.advengsoft.2013.12.007.
  • Nadeem, M.W., et al., 2020. Brain tumor analysis empowered with deep learning: a review, taxonomy, and future challenges. Brain Sciences, 10 (2), 118. doi:10.3390/brainsci10020118.
  • Pang, L., et al., 2020. Real-time concealed object detection from passive millimeter wave images based on the YOLOv3 algorithm. Sensors, 20 (6), 1678. doi:10.3390/s20061678.
  • Powerline Image Dataset. 2023. Available from: https://b2find.dkrz.de/dataset/e22af740-661e-5d74-b923-ed58661a41c0 [ Accessed September 2023].
  • Qu, G., Zhang, D., and Yan, P., 2001. Medical image fusion by wavelet transform modulus maxima. Optics Express, 9 (4), 184–190. doi:10.1364/OE.9.000184.
  • Shabani, A., et al., 2020. Search and rescue optimization algorithm: a new optimization method for solving constrained engineering optimization problems. Expert Systems with Applications, 161, 113698. doi:10.1016/j.eswa.2020.113698.
  • Shenfield, A., Day, D., and Ayesh, A., 2018. Intelligent intrusion detection systems using artificial neural networks. ICT Express, 4 (2), 95–99. doi:10.1016/j.icte.2018.04.003.
  • Shreyamsha Kumar, B.K., 2015. Image fusion based on pixel significance using cross bilateral filter. Signal, Image and Video Processing, 9 (5), 1193–1204. doi:10.1007/s11760-013-0556-9.
  • Sun, D., et al., 2019. Digital signal modulation recognition algorithm based on vggnet model. In 2019 IEEE 5th international conference on computer and communications (ICCC), Chengdu, China, IEEE, 1575–1579.
  • Usharani, A. and Bhavana, D., 2021. Deep convolution neural network based approach for multispectral images. International Journal of System Assurance Engineering & Management, 1–10. doi:10.1007/s13198-021-01133-8.
  • Wang, D., et al., 2016. Image fusion incorporating parameter estimation optimized Gaussian mixture model and fuzzy weighted evaluation system: a case study in time-series plantar pressure data set. IEEE Sensors Journal, 17 (5), 1407–1420. doi:10.1109/JSEN.2016.2641501.
  • Wang, L., Li, B., and Tian, L.F., 2014. EGGDD: an explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain. Information Fusion, 19, 29–37. doi:10.1016/j.inffus.2013.04.005.
  • Wu, Z., Shen, C., and Van Den Hengel, A., 2019. Wider or deeper: Revisiting the Resnet model for visual recognition. Pattern Recognition, 90, 119–133. doi:10.1016/j.patcog.2019.01.006.
  • Xiao, Y., et al., 2023. Adaptive multi-source data fusion vessel trajectory prediction model for intelligent maritime traffic. Knowledge-Based Systems, 277, 110799. doi:10.1016/j.knosys.2023.110799.
  • Zhang, H., et al., 2020. Faster R-CNN, fourth-order partial differential equation and global-local active contour model (FPDE-GLACM) for plaque segmentation in IV-OCT image. Signal, Image and Video Processing, 14 (3), 509–517. doi:10.1007/s11760-019-01578-2.

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.