红外和可见光图像融合文章整理

红外和可见光图像融合

本篇博文在转载:图像融合论文及代码网址整理总结(2)——红外与可见光图像融合的基础上进行了扩充,整理汇总一下现有的红外与可见光图像融合算法(文章和代码)。希望为自己以及大家查红外和可见光图像融合领域的文章代码提供一些便捷。另外,该领域的文章很多,本篇博文也只是整理了其中的一部分,由于水平有限,并未对文章进行解读!

 

转载作者同系列的博文还有:

图像融合论文及代码网址整理总结(1)——多聚焦图像融合

图像融合论文及代码网址整理总结(2)——红外与可见光图像融合

图像融合论文及代码网址整理总结(3)——题目中未加区分的图像融合算法

图像融合数据集,图像融合数据库

 

 

【2020】

1、文章:DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion  【深度学习】

Cite as:Ma J, Xu H, Jiang J, et al. DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion[J]. IEEE Transactions on Image Processing, 2020, 29: 4980-4995.

Paper:DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion

Code:https://github.com/jiayi-ma/DDcGAN

2、文章:Rethinking the Image Fusion A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity  【深度学习】【通用图像融合】

Cite as:Zhang H, Xu H, Xiao Y, et al. Rethinking the image fusion: A fast unified image fusion network based on proportional maintenance of gradient and intensity[C]//Proc. AAAI Conf. Artif. Intell. 2020.

Paper:Rethinking the image fusion: A fast unified image fusion network based on proportional maintenance of gradient and intensity(PMGI)

Code:https://github.com/HaoZhang1018/PMGI AAAI2020

3、文章:Infrared and visible image fusion based on target-enhanced multiscale transform decomposition  【多尺度分解】

Cite as:Chen J, Li X, Luo L, et al. Infrared and visible image fusion based on target-enhanced multiscale transform decomposition[J]. Information Sciences, 2020, 508: 64-78.

Paper:Infrared and visible image fusion based on target-enhanced multiscale transform decomposition

Code:https://github.com/jiayi-ma/DDcGAN

4、文章:MDLatLRR: A novel decomposition method for infrared and visible image fusion  【多尺度分解】

Cite as:Li H, Wu X, Kittler J, et al. MDLatLRR: A Novel Decomposition Method for Infrared and Visible Image Fusion[J]. IEEE Transactions on Image Processing, 2020: 4733-4746.

Paper:IMDLatLRR: A novel decomposition method for infrared and visible image fusion

Code:https://github.com/hli1221/imagefusion_mdlatlrr

5、文章:IFCNN: A general image fusion framework based on convolutional neural network  【深度学习】【通用图像融合】

Cite as:Zhang Y, Liu Y, Sun P, et al. IFCNN: A General Image Fusion Framework Based on Convolutional Neural Network[J]. Information Fusion, 2020: 99-118.

Paper:. IFCNN: A General Image Fusion Framework Based on Convolutional Neural Network

Code:https://github.com/uzeful/IFCNN

【2019】

1、文章:FusionGAN:A generative adversarial network for infrared and visible image fusion  【深度学习】

Cite as:Jiayi Ma, Wei Yu, Pengwei Liang, Chang Li, and Junjun Jiang. FusionGAN: A generative adversarial network for infrared and visible image fusion, Information Fusion, 48, pp. 11-26, Aug. 2019.

Paper:https://doi.org/10.1016/j.inffus.2018.09.004

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

作者:

马佳义,武汉大学。

个人主页:

http://www.escience.cn/people/jiayima/index.html (科研在线 科研主页)

http://mvp.whu.edu.cn/jiayima/

GitHub地址:https://github.com/jiayi-ma

李畅,合肥工业大学,讲师。

个人主页:http://www.escience.cn/people/lichang/index.html(科研在线 科研主页)

(值得一提:主页内Data栏总结了高光谱图像数据链接。)

 GitHub地址:https://github.com/Chang-Li-HFUT

江俊君,哈尔滨工业大学,教授。

个人主页:

http://www.escience.cn/people/jiangjunjun/index.html(科研在线 科研主页)

https://jiangjunjun.wordpress.com

http://homepage.hit.edu.cn/jiangjunjun(哈工大主页)

https://scholar.google.com/citations?user=WNH2_rgAAAAJ&hl=zh-CN&oi=ao(Google学术主页)

https://github.com/junjun-jiang(GitHub主页)

 

2、文章:Infrared and visible image fusion methods and applications: A survey 【综述文章】

Cite as: Jiayi Ma, Yong Ma, and Chang Li. "Infrared and visible image fusion methods and applications: A survey", Information Fusion, 45, pp. 153-178, 2019.

Paper:https://doi.org/10.1016/j.inffus.2018.02.004

作者:马佳义,武汉大学。马泳李畅

 

【2018】

1、文章:Infrared and Visible Image Fusion with ResNet and zero-phase component analysis(点击下载文章)【深度学习】

Cite as:Li H , Wu X J , Durrani T S . Infrared and Visible Image Fusion with ResNet and zero-phase component analysis[J]. 2018.

Paper:https://arxiv.org/abs/1806.07119

Code:https://github.com/hli1221/imagefusion_resnet50

作者:

李辉,江南大学博士。(导师:吴小俊

主页:https://hli1221.github.io

GitHub地址:

https://github.com/hli1221 (primary GitHub)

https://github.com/exceptionLi

吴小俊

主页:http://iot.jiangnan.edu.cn/info/1059/1532.htm(学校导师主页)

https://scholar.google.com/citations?user=5IST34sAAAAJ&hl=zh-CN&oi=sra(Google学术主页)

 

2、文章:DenseFuse: A Fusion Approach to Infrared and Visible Images(点击下载文章)【深度学习】

Cite as:

H. Li, X. J. Wu, DenseFuse: A Fusion Approach to Infrared and Visible Images, IEEE Trans. Image Process.(Early Access), pp. 1-1, 2018.

Paper:https://arxiv.org/abs/1804.08361

(DOI:10.1109/TIP.2018.2887342

Code:https://github.com/hli1221/imagefusion_densefuse

另一个实现:https://github.com/srinu007/MultiModelImageFusion(代码包里也包含有图像融合MATLAB客观评价指标函数)

作者:李辉,江南大学博士。(导师:吴小俊

 

3、文章:Infrared and Visible Image Fusion using a Deep Learning Framework(点击下载文章)【深度学习】

Cite as:Li H, Wu X J, Kittler J. Infrared and Visible Image Fusion using a Deep Learning Framework[C]//Pattern Recognition (ICPR), 2018 24rd International Conference on. IEEE, 2018: 2705 - 2710.

Paper:https://arxiv.org/pdf/1804.06992

DOI: 10.1109/ICPR.2018.8546006

Code:https://github.com/hli1221/imagefusion_deeplearning

作者:李辉,江南大学博士。(导师:吴小俊

 

4、文章:Infrared and visible image fusion using Latent Low-Rank Representation     【LRR用于图像融合】

Cite as:Li H, Wu X J. Infrared and visible image fusion using Latent Low-Rank Representation[J]. 2018.

Paper:https://arxiv.org/abs/1804.08992

Code:https://github.com/exceptionLi/imagefusion_Infrared_visible_latlrr

作者:李辉,江南大学博士。(导师:吴小俊

 

5、文章:Infrared and visible image fusion using a novel deep decomposition method【深度学习】

Cite as: Li H, Wu X. Infrared and visible image fusion using a novel deep decomposition method[J]. arXiv: Computer Vision and Pattern Recognition, 2018.

Paper:https://arxiv.org/abs/1811.02291

Code:https://github.com/hli1221/imagefusion_deepdecomposition

作者:李辉,江南大学博士。(导师:吴小俊

 

6、文章:Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain

Cite as: Jin X, Jiang Q, Yao S, et al. Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain[J]. Infrared Physics & Technology, 2018: 1-12.

Paper:https://doi.org/10.1016/j.infrared.2017.10.004

Code:https://github.com/jinxinhuo/SWT_DCT_SF-for-image-fusion

https://ww2.mathworks.cn/matlabcentral/fileexchange/68674-infrared-and-visual-image-fusion-method-based-on-swt_dct_sf?s_tid=FX_rc2_behav

作者:金鑫——2013级云南大学博士。

 

7、文章:Multi-scale decomposition based fusion of infrared and visible image via total variation and saliency analysis

Cite as: Ma T, Ma J, Fang B, et al. Multi-scale decomposition based fusion of infrared and visible image via total variation and saliency analysis[J]. Infrared Physics & Technology, 2018: 154-162.

Paper:https://doi.org/10.1016/j.infrared.2018.06.002

作者:Siwen Quan (权思文)

主页:https://sites.google.com/view/siwenquanshomepage

https://scholar.google.com/citations?user=9CS008EAAAAJ&hl=zh-CN&oi=sra(Google学术主页)

 

8、文章:Visible and infrared image fusion using DTCWT and adaptive combined clustered dictionary

Cite as: Aishwarya N, Thangammal C B. Visible and infrared image fusion using DTCWT and adaptive combined clustered dictionary[J]. Infrared Physics & Technology, 2018: 300-309.

Paper:https://doi.org/10.1016/j.infrared.2018.08.013

 

9、文章:Infrared and visible image fusion based on convolutional neural network model and saliency detection via hybrid l0-l1 layer decomposition 【CNN】【深度学习】【显著性检测】

Cite as: Liu D, Zhou D, Nie R, et al. Infrared and visible image fusion based on convolutional neural network model and saliency detection via hybrid l0-l1 layer decomposition[J]. Journal of Electronic Imaging, 2018, 27(06).

Paper:https://doi.org/10.1117/1.JEI.27.6.063036

作者:

周冬明——云南大学教授,博导
聂仁灿——云南大学信息学院副教授,博士,硕士生导师 

 

【2017】

1、文章:Fusion of visible and infrared images using global entropy and gradient constrained regularization

Paper:https://doi.org/10.1016/j.infrared.2017.01.012

作者:赵巨峰,杭州电子科技大学副教授,硕导。

个人主页:http://mypage.hdu.edu.cn/zhaojufeng/0.html

 

2、文章:A survey of infrared and visual image fusion methods   【综述文章】

Paper:https://doi.org/10.1016/j.infrared.2017.07.010

作者:

金鑫——2013级云南大学博士。
姚邵文——云南大学软件学院院长
周冬明——云南大学教授,博导
聂仁灿——云南大学信息学院副教授,博士,硕士生导师 

贺康建——2014级云南大学博士

 

3、文章:Infrared and Visual Image Fusion through Infrared Feature Extraction and Visual Information Preservation

Cite as:

Yu Zhang, Lijia Zhang, Xiangzhi Bai and Li Zhang. Infrared and Visual Image Fusion through Infrared Feature Extraction and Visual Information Preservation, Infrared Physics & Technology 83 (2017) 227-237.

Paper:http://dx.doi.org/10.1016/j.infrared.2017.05.007(DOI:10.1016/j.infrared.2017.05.007)

Code:https://github.com/uzeful/Infrared-and-Visual-Image-Fusion-via-Infrared-Feature-Extraction-and-Visual-Information-Preservation

作者:张余,清华大学博士。

主页:

https://sites.google.com/site/uze1989/

https://uzeful.github.io/

GitHub地址:https://github.com/uzeful

 

4、文章:Visible and NIR image fusion using weight-map-guided Laplacian–Gaussian pyramid for improving scene visibility

Cite as:

Vanmali A V , Gadre V M . Visible and NIR image fusion using weight-map-guided Laplacian–Gaussian pyramid for improving scene visibility[J]. Sādhanā, 2017, 42(7):1063-1082.

Paper: (DOI:10.1007/s12046-017-0673-1)

Code:https://drive.google.com/file/d/0B-hGkOHjv3gzVnU5Slg2YWZRWVE/view?usp=sharing

 

5、文章:Infrared and visible image fusion based on visual saliency map and weighted least square optimization

Cite as:

Ma J, Zhou Z, Wang B, et al. Infrared and visible image fusion based on visual saliency map and weighted least square optimization[J]. Infrared Physics & Technology, 2017, 82:8-17.

Paper:https://doi.org/10.1016/j.infrared.2017.02.005(DOI:10.1016/j.infrared.2017.02.005)

Code:https://github.com/JinleiMa/Image-fusion-with-VSM-and-WLS

作者:马金磊,北京理工大学。

GitHub地址:https://github.com/JinleiMa?utf8=

 

6、文章:Infrared and visible image fusion method based on saliency detection in sparse domain

Cite as:

Liu C H , Qi Y , Ding W R . Infrared and visible image fusion method based on saliency detection in sparse domain[J]. Infrared Physics & Technology, 2017:S1350449516307150.

Paper:https://doi.org/10.1016/j.infrared.2017.04.018(DOI:10.1016/j.infrared.2017.04.018)

 

7、文章:Infrared and visible image fusion with convolutional neural networks 【深度学习】【CNN】

Cite as:

Yu Liu, Xun Chen, Juan Cheng, Hu Peng, Zengfu Wang,“Infrared and visible image fusion with convolutional neural networks”, International Journal of Wavelets,Multiresolution and Information Processing, vol. 16, no. 3, 1850018: 1-20, 2018.

Paper:https://www.worldscientific.com/doi/abs/10.1142/S0219691318500182

https://www.researchgate.net/publication/321799375_Infrared_and_visible_image_fusion_with_convolutional_neural_networks

(DOI:10.1142/S0219691318500182)

Code:http://www.escience.cn/people/liuyu1/Codes.html(刘羽)

作者:

刘羽

陈勋,教授、博导

http://staff.ustc.edu.cn/~xunchen/

https://scholar.google.com/citations?user=aBnUWyQAAAAJ&hl=zh-CN&oi=sra(Google学术主页)

成娟

http://www.escience.cn/people/chengjuanhfut/index.html

https://scholar.google.com/citations?user=fMOOhH8AAAAJ&hl=zh-CN&oi=sra(Google学术主页)

 

8、文章:Infrared and visible image fusion based on total variation and augmented Lagrangian

Paper:https://doi.org/10.1364/JOSAA.34.001961

作者:HANQI GUO, YONG MA(马泳), XIAOGUANG MEI(梅晓光), JIAYI MA(马佳义),武汉大学。

 

9、文章:Fusion of infrared-visible images using improved multi-scale top-hat transform and suitable fusion rules

Paper:https://doi.org/10.1016/j.infrared.2017.01.013

 

10、Fusion of infrared and visible images based on nonsubsampled contourlet transform and sparse K-SVD dictionary learning

Paper:(DOI:10.1016/j.infrared.2017.01.026)

作者:

Jiajun Cai,武汉大学

https://c.glgoo.top/citations?user=1jAmUp0AAAAJ&hl=zh-CN&oi=sra

 

 

【2016】

1、文章:Infrared and visible image fusion via gradient transfer and total variation minimization(点击下载文章)

Cite as:

Jiayi Ma, Chen Chen, Chang Li, and Jun Huang. Infrared and visible image fusion via gradient transfer and total variation minimization, Information Fusion, 31, pp. 100-109, Sept. 2016.

Paper:https://doi.org/10.1016/j.inffus.2016.02.001

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

(代码包里也提供了论文中用作对比实验的其他八种算法的代码,以及图像融合MATLAB客观评价指标函数)

作者:马佳义,武汉大学。

个人主页:http://www.escience.cn/people/jiayima/index.html

 

2、文章:Multi-window visual saliency extraction for fusion of visible and infrared images

Cite as:

Zhao J , Gao X , Chen Y , et al. Multi-window visual saliency extraction for fusion of visible and infrared images[J]. Infrared Physics & Technology, 2016, 76:295-302.

Paper:https://doi.org/10.1016/j.infrared.2016.01.020

作者:赵巨峰,杭州电子科技大学副教授,硕导。

个人主页:http://mypage.hdu.edu.cn/zhaojufeng/0.html

 

3、文章:Two-scale image fusion of visible and infrared images using saliency detection

Cite as:

Bavirisetti D P , Dhuli R . Two-scale image fusion of visible and infrared images using saliency detection[J]. Infrared Physics & Technology, 2016, 76:52-64.

Paper:https://doi.org/10.1016/j.infrared.2016.01.009

Code:https://www.mathworks.com/matlabcentral/fileexchange/63571-two-scale-image-fusion-of-visible-and-infrared-images-using-saliency-detection

作者:Durga Prasad Bavirisetti

主页:https://sites.google.com/view/durgaprasadbavirisetti/home

主页中右上角Datasets中提供了各种图像融合数据集。

https://scholar.google.com/citations?user=hc0VdQQAAAAJ&hl=zh-CN&oi=sra(Google学术主页)

 

4、文章:Fusion of Infrared and Visible Sensor Images Based on Anisotropic Diffusion and Karhunen-Loeve Transform

Paper:https://ieeexplore.ieee.org/document/7264981

DOI: 10.1109/JSEN.2015.2478655

Code:https://ww2.mathworks.cn/matlabcentral/fileexchange/63591-fusion-of-infrared-and-visible-sensor-images-based-on-anisotropic-diffusion-and-kl-transform?s_tid=FX_rc2_behav

作者:Durga Prasad Bavirisetti

主页:https://sites.google.com/view/durgaprasadbavirisetti/home

主页中右上角Datasets中提供了各种图像融合数据集。

https://scholar.google.com/citations?user=hc0VdQQAAAAJ&hl=zh-CN&oi=sra(Google学术主页)

 

5、文章:Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters     【HMSD】

Cite as:

Zhiqiang Zhou et al. "Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters", Information Fusion, 30, 2016

Paper:https://doi.org/10.1016/j.inffus.2015.11.003

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

或:https://www.researchgate.net/publication/304246314

作者:周志强,北京理工大学自动化学院,副教授

主页:http://ac.bit.edu.cn/szdw/jsdw/mssbyznxtyjs_20150206131517284801/20150206115445413049_20150206131517284801/index.htm

GitHub地址:https://github.com/bitzhouzq

 

6、文章:Fusion of infrared and visible images for night-vision context enhancement

Paper:https://doi.org/10.1364/AO.55.006480

Code:https://github.com/bitzhouzq/Context-Enhance-via-Fusion

作者:周志强,北京理工大学自动化学院,副教授

主页:http://ac.bit.edu.cn/szdw/jsdw/mssbyznxtyjs_20150206131517284801/20150206115445413049_20150206131517284801/index.htm

GitHub地址:https://github.com/bitzhouzq

 

【2015】

1、文章:Attention-based hierarchical fusion of visible and infrared images

Paper:https://doi.org/10.1016/j.ijleo.2015.08.120

作者:

陈艳菲,副教授,硕士生导师。

主页:http://eie.wit.edu.cn/info/1067/1028.htm(教师主页)

桑农,华中科技大学自动化学院教授,博士生导师

主页:http://auto.hust.edu.cn/info/1154/3414.htm(教师主页)

 

【2014】

1、文章:Fusion method for infrared and visible images by using non-negative sparse representation     【NNSR】

Cite as:

Wang J , Peng J , Feng X , et al. Fusion method for infrared and visible images by using non-negative sparse representation[J]. Infrared Physics & Technology, 2014, 67:477-489.

Paper:https://doi.org/10.1016/j.infrared.2014.09.019

作者:西北工业大学 王珺彭进业冯晓毅何贵青

 

2、文章:The infrared and visible image fusion algorithm based on target separation and sparse representation

Cite as:

Lu X , Zhang B , Zhao Y , et al. The infrared and visible image fusion algorithm based on target separation and sparse representation[J]. Infrared Physics & Technology, 2014, 67:397-407.

Paper:https://doi.org/10.1016/j.infrared.2014.09.007

作者:吕晓琪,张宝华,赵瑛,内蒙古科技大学

吕晓琪,内蒙古科技大学信息工程学院教授,博导。

主页:http://graduate.imust.cn/info/1063/2860.htm

张宝华,内蒙古科技大学信息工程学院副教授,硕导。

主页:http://graduate.imust.cn/info/1063/2331.htm

赵瑛,内蒙古科技大学信息工程学院讲师,硕导。

主页:http://graduate.imust.cn/info/1063/2409.htm

 

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PS:早期的代码中用到的某些函数可能随着MATLAB版本的升级更新,会被删掉,导致运行错误。解决办法就是在自己电脑上保留着低版本的MATLAB。然后用到哪个函数,复制出来粘贴到代码文件夹里。

由于笔者水平有限,某些最新的论文未被收集整理,欢迎大家讨论交流!

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