Table 1 Traditional and DL methods are listed with their corresponding reference number and code URL that was provided by the authors

Traditional

directional discrete cosine transform and principal component analysis (DDCT-PCA)

[14]

https://www.mathworks.com/matlabcentral/fileexchange/46169-directional-discrete-cosine-transform-and-principal-component-analysis-based-image-fusion

hybrid multi-scale decomposition (HMSD)

[13]

https://github.com/bitzhouzq/Hybrid-MSD-Fusion

fourth-order partial differential equations (FPDE)

[15]

https://www.mathworks.com/matlabcentral/fileexchange/63570-multi-sensor-image-fusion-based-on-fourth-order-partial-differential-equations

gradient transfer fusion (GTF)

[47]

https://github.com/jiayi-ma/GTF

multi-exposure image fusion (MEF)

[48]

https://github.com/tkd1088/multi-exposure-image-fusion

infrared and visible image fusion (IVF)

[49]

https://github.com/LYJ903118120/IVFusion

multi-focus images fusion (GFDF)

[50]

https://github.com/bitname/Multi-focus-image-fusion-GFDF

Deep learning

CNN-Fuse

[51]

https://github.com/budaoxiaowanzi/image-fusion

CU-Net

[52]

https://github.com/cindydeng1991/TPAMI-CU-Net

SESF-Fuse

[53]

https://github.com/Keep-Passion/SESF-Fuse

DSAGAN

[54]

https://github.com/jeffsonfu/DSAGAN

U2Fusion

[55]

https://github.com/hanna-xu/U2Fusion

SwinFusion

[56]

https://github.com/Linfeng-Tang/SwinFusion

IFCNN

[57]

https://github.com/uzeful/IFCNN

FusionGAN

[35]

https://github.com/jiayi-ma/FusionGAN