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A Detailed Survey of Multi Focus Image Fusion

by Kashif Siddiqui, Amit Saxena, Kaptan Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 12
Year of Publication: 2024
Authors: Kashif Siddiqui, Amit Saxena, Kaptan Singh
10.5120/ijca2024923503

Kashif Siddiqui, Amit Saxena, Kaptan Singh . A Detailed Survey of Multi Focus Image Fusion. International Journal of Computer Applications. 186, 12 ( Mar 2024), 25-30. DOI=10.5120/ijca2024923503

@article{ 10.5120/ijca2024923503,
author = { Kashif Siddiqui, Amit Saxena, Kaptan Singh },
title = { A Detailed Survey of Multi Focus Image Fusion },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2024 },
volume = { 186 },
number = { 12 },
month = { Mar },
year = { 2024 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number12/a-detailed-survey-of-multi-focus-image-fusion/ },
doi = { 10.5120/ijca2024923503 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-03-27T00:44:31.515175+05:30
%A Kashif Siddiqui
%A Amit Saxena
%A Kaptan Singh
%T A Detailed Survey of Multi Focus Image Fusion
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 12
%P 25-30
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Multi-focus image fusion is a crucial aspect of image processing, aimed at enhancing the overall visual quality and information content of images captured at different focal planes. This paper presents a comprehensive survey of various techniques and methodologies employed in the domain of multi-focus image fusion. The paper begins by explaining the fundamental concepts and challenges associated with image fusion. It then proceeds to categorize existing methodologies of image fusion. Then it explains about multi focus image fusion and with their types and recent proposed techniques developed by researchers. Furthermore, the survey evaluates the strengths and limitations of each technique, providing insights into their applicability under varying conditions. This survey serves as a valuable resource for researchers, practitioners, and enthusiasts interested in the advancements and trends in multi-focus image fusion. By synthesizing and organizing the vast array of techniques available, the paper aims to facilitate a deeper understanding of the subject and inspire further innovation in the pursuit of optimal solutions for multi-focus image fusion challenges.

References
  1. Vakaimalar E, Mala K & Suresh Babu R Multifocus image fusion scheme based on discrete cosine transform and spatial frequency. Multimed Tools Appl 78, 17573–17587 (2019). https://doi.org/10.1007/s11042-018-7124-9
  2. Yang Y, Tong S, Huang S, Lin P : Multifocus image fusion based on NSCT and focused area detection. IEEE Sensors J 15(5):2824–2838 (2015). https://doi.org/10.1109/JSEN.2014.2380153
  3. Liu Y, Chen X, Peng H, Wang Z : Multi-focus image fusion with a deep convolutional neural network. Inf Fusion 36:191–207 (2017).
  4. S. Mahapatra, K. D. Sa and D. Dash : DCT Based Multifocus Image Fusion for Wireless Sensor Networks," 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, India, pp. 871-875 (2018). doi: 10.1109/ICICCT.2018.8473005.
  5. Sale, D. An enhanced image fusion in the spatial domain based on modified independent component analysis. Multimed Tools Appl 81, 44123–44140 (2022). https://doi.org/10.1007/s11042-022-13238-8
  6. Hui Wan, Xianlun Tang, Zhiqin Zhu, Bin Xiao and Weisheng Li, “Multi-Focus Color Image Fusion Based on Quaternion Multi-Scale Singular Value Decomposition”, Front. Neurorobot. 15:695960. Vol. 15 June (2021). doi: 10.3389/fnbot.2021.695960
  7. Ma, J., Zhou, Z., Wang, B., Miao, L., and Zong, H. : Multi-focus image fusion using boosted random walks-based algorithm with twoscale focus maps. Neurocomputing 335, 9–20 (2019). doi: 10.1016/j.neucom.201 9.01.048
  8. An, F., and Li, Z. : Image processing algorithm based on bidimensional local mean decomposition. J. Math. Imaging VIS 61, 1243–1257 (2019). doi: 10.1007/s10851-019-00899-8
  9. M. Amin-Naji, P. Ranjbar-Noiey and A. Aghagolzadeh : Multi-focus image fusion using Singular Value Decomposition in DCT domain, 10th Iranian Conference on Machine Vision and Image Processing (MVIP), Isfahan, Iran, pp. 45-51 (2017). doi: 10.1109/IranianMVIP.2017.8342367.
  10. XixiNie, Bin Xiao, Xiuli Bi, Weisheng Li, XinboGao : A focus measure in discrete cosine transform domain for multi-focus image fast fusion", Neurocomputing, Volume 465, Pages 93-102, (2021).https://doi.org/10.1016/j.neucom.2021.08.109.
  11. Zhou, Y.; Yu, L.; Zhi, C.; Huang, C.; Wang, S.; Zhu, M.; Ke, Z.; Gao, Z.; Zhang, Y.; Fu, S. A Survey of Multi-Focus Image Fusion Methods. Appl. Sci., 12, 6281 (2022). https://doi.org/10.3390/app12126281
  12. Wan H, Tang X, Zhu Z, Li W. Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary. Entropy (Basel), Oct 19;23(10):1362 (2021). doi: 10.3390/e23101362. PMID: 34682086; PMCID: PMC8534655.
  13. Joshi, Kapil and Kirola, Madhu and Chaudhary, Sumit and Diwakar, Manoj and Joshi, N.K., Multi-Focus Image Fusion Using Discrete Wavelet Transform Method (March 14, 2019). International Conference on Advances in Engineering Science Management & Technology ICAESMT, Uttaranchal University, Dehradun, India, (2019). Available at SSRN: https://ssrn.com/abstract=3383141 or http://dx.doi.org/10.2139/ssrn.3383141
  14. N. Taxak and S. Singhal : High PSNR based Image Fusion by Weighted Average Brovery Transform Method, Devices for Integrated Circuit (DevIC), Kalyani, India, pp. 451-455 (2019). doi: 10.1109/DEVIC.2019.8783400.
  15. Xuan, SB., Sang, GL., Zhao, B., Zheng, ZG.:Non-sampling Contourlet Based “Consistency Verification” Method of Image Fusion. In: Huang, DS.,Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24728-6_46
  16. X. Li, F. Zhou and J. Li : Multi-focus Image Fusion Based on the Filtering Techniques and Block Consistency Verification, IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), Chongqing, China, 2018, pp. 453-457 (2018). doi: 10.1109/ICIVC.2018.8492825.
  17. W. Tang, F. He, Y. Liu and Y. Duan : MATR: Multimodal Medical Image Fusion via Multiscale Adaptive Transformer," in IEEE Transactions on Image Processing, vol. 31, pp. 5134-5149, (2022). doi: 10.1109/TIP.2022.3193288.
  18. Kanika Bhalla, Deepika Koundal, Bhisham Sharma, Yu-Chen Hu, Atef Zaguia : A fuzzy convolutional neural network for enhancing multi-focus image fusion, Journal of Visual Communication and Image Representation, Volume 84, 103485, ISSN 1047-3203, (2022). https://doi.org/10.1016/j.jvcir.2022.103485.
  19. Liu, S., Ma, J., Yang, Y., Qiu, T., Li, H., Hu, S., & Zhang, Y. D.: A multi-focus color image fusion algorithm based on low vision image reconstruction and focused feature extraction. Signal Processing: Image Communication, 100, 116533, (2022).
Index Terms

Computer Science
Information Sciences

Keywords

Multi focus Image Fusion image processing medical imaging

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