CLC number: TP302.4
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2020-03-26
Cited: 0
Clicked: 5402
Xue-feng Zhang, Hui Yan, Hao He. Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(6): 834-843.
@article{title="Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets",
author="Xue-feng Zhang, Hui Yan, Hao He",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="6",
pages="834-843",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900737"
}
%0 Journal Article
%T Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets
%A Xue-feng Zhang
%A Hui Yan
%A Hao He
%J Frontiers of Information Technology & Electronic Engineering
%V 21
%N 6
%P 834-843
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900737
TY - JOUR
T1 - Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets
A1 - Xue-feng Zhang
A1 - Hui Yan
A1 - Hao He
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 6
SP - 834
EP - 843
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1900737
Abstract: Multi-focus image fusion is an increasingly important component in image fusion, and it plays a key role in imaging. In this paper, we put forward a novel multi-focus image fusion method which employs fractional-order derivative and intuitionistic fuzzy sets. The original image is decomposed into a base layer and a detail layer. Furthermore, a new fractional-order spatial frequency is built to reflect the clarity of the image. The fractional-order spatial frequency is used as a rule for detail layers fusion, and intuitionistic fuzzy sets are introduced to fuse base layers. Experimental results demonstrate that the proposed fusion method outperforms the state-of-the-art methods for multi-focus image fusion.
[1]Atanassov KT, 1986. Intuitionistic fuzzy sets. Fuzzy Sets Syst, 20(1):87-96.
[2]Azarang A, Ghassemian H, 2018. Application of fractional-order differentiation in multispectral image fusion. Remote Sens Lett, 9(1):91-100.
[3]Bai J, Feng XC, 2007. Fractional-order anisotropic diffusion for image denoising. IEEE Trans Image Process, 16(10):2492-2502.
[4]Balasubramaniam P, Ananthi VP, 2014. Image fusion using intuitionistic fuzzy sets. Inform Fus, 20:21-30.
[5]Baleanu D, Wu GC, 2019. Some further results of the Laplace transform for variable-order fractional difference equations. Fract Calc Appl Anal, 22(6):180-192.
[6]Chen DL, Chen YQ, Xue DY, 2015. Fractional-order total variation image denoising based on proximity algorithm. Appl Math Comput, 257:537-545.
[7]Chen Y, Qin Z, 2015. Gradient-based compressive image fusion. Front Inform Technol Electron Eng, 16(3):227-237.
[8]Eskicioglu AM, Fisher PS, 1995. Image quality measures and their performance. IEEE Trans Commun, 43(12):2959-2965.
[9]Huang W, Jing ZL, 2007. Multi-focus image fusion using pulse coupled neural network. Patt Recogn Lett, 28(9):1123-1132.
[10]Li ST, Yang B, 2008. Multifocus image fusion using region segmentation and spatial frequency. Image Vis Comput, 26(7):971-979.
[11]Li ST, Kwok JT, Wang YN, 2001. Combination of images with diverse focuses using the spatial frequency. Inform Fus, 2(3):169-176.
[12]Li ST, Kang XD, Hu JW, 2013. Image fusion with guided filtering. IEEE Trans Image Process, 22(7):2864-2875.
[13]Podlubny I, 1999. Fractional Differential Equations: Mathematics in Science and Engineering. Academic Press, San Diego, USA.
[14]Pu T, Ni GQ, 2000. Contrast-based image fusion using the discrete wavelet transform. Opt Eng, 39(8):2075-2082.
[15]Pu YF, Wang WX, 2007. Fractional differential masks of digital image and their numerical implementation algorithms. Acta Autom Sin, 33(11):1128-1135 (in Chinese).
[16]Pu YF, Zhou JL, Yuan X, et al., 2010. Fractional differential mask: a fractional differential-based approach for multiscale texture enhancement. IEEE Trans Image Process, 19(2):491-511.
[17]Tao R, Deng B, Wang Y, 2006. Research progress of the fractional Fourier transform in signal processing. Sci China Ser F, 49(1):1-25.
[18]Wu GC, Deng ZG, Baleanu D, et al., 2019. New variable-order fractional chaotic systems for fast image encryption. Chaos, 29(8):083103.
[19]Xu ZS, 2007. Intuitionistic fuzzy aggregation operators. IEEE Trans Fuzzy Syst, 15(6):1179-1187.
[20]Yang B, Li ST, 2007. Multi-focus image fusion based on spatial frequency and morphological operators. Chin Opt Lett, 5(8):452-453.
[21]Yang Y, Que Y, Huang SY, et al., 2016. Multimodal sensor medical image fusion based on type-2 fuzzy logic in NSCT domain. IEEE Sens J, 16(10):3735-3745.
[22]Zadeh LA, 1965. Fuzzy sets. Inform Contr, 8(3):338-353.
[23]Zhang L, Liu P, Liu YL, et al., 2010. High quality multi-focus polychromatic composite image fusion algorithm based on filtering in frequency domain and synthesis in space domain. J Zhejiang Univ-Sci C (Comput &Electron), 11(5):365-374.
[24]Zhang XF, Chen YQ, 2018. Admissibility and robust stabilization of continuous linear singular fractional order systems with the fractional order α: the 0<α<1 case. ISA Trans, 82:42-50.
[25]Zhu K, Liu G, Zhao L, et al., 2017. Label fusion for segmentation via patch based on local weighted voting. Front Inform Technol Electron Eng, 18(5):680-688.
Open peer comments: Debate/Discuss/Question/Opinion
<1>