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Methods

1 PerceptualFusion

Fu, Yu, Xiao-Jun Wu, and Tariq Durrani. "Image fusion based on generative adversarial network consistent with perception." Information Fusion (2021).

@article{fu2021image,
  title={Image fusion based on generative adversarial network consistent with perception},
  author={Fu, Yu and Wu, Xiao-Jun and Durrani, Tariq},
  journal={Information Fusion},
  year={2021},
  publisher={Elsevier}
}

2 Dualbranch_Fusion

@inproceedings{fu2021dual,
  title={A Dual-branch Network for Infrared and Visible Image Fusion},
  author={Fu, Yu and Wu, Xiao-Jun},
  booktitle={2020 25th International Conference on Pattern Recognition},
  year={2020}
}

3 DeepDecFusion

@article{fu2021deep,
  title={A Deep Decomposition Network for Image Processing: A Case Study for Visible and Infrared Image Fusion},
  author={Fu, Yu and Wu, Xiao-Jun and Kittler, Josef},
  journal={arXiv preprint arXiv:2102.10526},
  year={2021}
}

4 An Effective Method for Fusing Infrared and Visible Images.

(later)

5 PPT Fusion

(later)

run

"main.m"

代码没写注释，有点乱

1.多进程

默认开启了多进程，核心为5个，

如果不需要，注释第二行和最后一行，以及将parfor改成for

line1: p = parpool('local',5) ;
......
line13: parfor ->>>  for
......
line62: delete(gcp('nocreate'));

2.多个文件夹评价

设置这里可以进行多个文件夹的评价

line5: fusion_name = ["0","5","10","15","20"];

比如，多种方法可以写成

line5: fusion_name = ["CVT","DCWT","Deepfuse"..........];

比如，多次迭代的结果可以写成

line5: fusion_name = ["0","5","10","15","20"];

然后由第8,9行来控制评价的文件夹

for fm=1:5
    name = fusion_name(fm);

输入图像

%         source_ir  = ['../TNO/ir/',num2str(i),'.bmp'];
%         source_vis = ['../TNO/vi/',num2str(i),'.bmp'];
source_ir  = ['../road/ir/',num2str(i),'.jpg'];
source_vis = ['../road/vi/',num2str(i),'.jpg'];
        
fused = strcat(fused_path,name,'/road/sm/',num2str(i),'.bmp');

输出结果

在所在文件夹保存成.mat文件

    save_path = strcat(fused_path,'/',name);
    save(save_path,'a','b') ;
    
save_path = strcat(fused_path,'/all');
save(save_path,'c') ;

然后用excel自己处理吧。

这是表头

EI	CrossEntropy	SF	EN	Qabf	SCD	FMI_w	FMI_dct	SSIM	MS_SSIM	FMI_pixel	Nabf	MI	VIF	SD	EN	DF	QSF	QMI	QS	QY	QC	QNCIE	Q^{AB/F}	AG	MIabf	QG	CC	VIFF	QP	QW	QE	QCV	QCB

=======================

run

"main.m"

The code is not commented, it's a bit messy

1. Multi-process

Multi-process is enabled by default, with 5 cores,

If not needed, comment the second and last lines, and change parfor to for

line1: p = parpool('local',5);
......
line13: parfor ->>> for
......
line62: delete(gcp('nocreate'));

2. Multiple folder evaluation

Set here to evaluate multiple folders

line5: fusion_name = ["0","5","10","15","20"];

For example, multiple methods can be written as

line5: fusion_name = ["CVT","DCWT","Deepfuse"..........];

For example, the result of multiple iterations can be written as

line5: fusion_name = ["0","5","10","15","20"];

Then lines 8 and 9 control the evaluation folder

for fm=1:5
    name = fusion_name(fm);

Input image

% source_ir = ['../TNO/ir/',num2str(i),'.bmp'];
% source_vis = ['../TNO/vi/',num2str(i),'.bmp'];
source_ir = ['../road/ir/',num2str(i),'.jpg'];
source_vis = ['../road/vi/',num2str(i),'.jpg'];
        
fused = strcat(fused_path,name,'/road/sm/',num2str(i),'.bmp');

Output result

Save as a .mat file in the folder where it is located

    save_path = strcat(fused_path,'/',name);
    save(save_path,'a','b');
    
save_path = strcat(fused_path,'/all');
save(save_path,'c');

Then use excel to handle it yourself.

This is the header

EI	CrossEntropy	SF	EN	Qabf	SCD	FMI_w	FMI_dct	SSIM	MS_SSIM	FMI_pixel	Nabf	MI	VIF	SD	EN	DF	QSF	QMI	QS	QY	QC	QNCIE	Q^{ AB/F}	AG	MIabf	QG	CC	VIFF	QP	QW	QE	QCV	QCB

thfylsty/Objective-evaluation-for-image-fusion