1 |
T. Pu and G. Ni, "Contrast-based image fusion using the discrete wavelet transform," Optical Engineering, vol. 39, no. 8, pp. 2075-2082, 2000.
DOI
|
2 |
S. Balakrishnan, M. Cacciola, L. Udpa, B. P. Rao, T. Jayakumar and B. Raj, "Development of image fusion methodology using discrete wavelet transform for eddy current images," Ndt & E International, vol. 51, no. 10, pp. 51-57, 2012.
DOI
|
3 |
C. Liu, L. Jin, H. Tao, G. Li, Z. Zhuang and Zhang, Y, "Multi-focus image fusion based on spatial frequency in discrete cosine transform domain," IEEE Signal Processing Letters, vol. 22, no. 2, pp. 220-224, 2015.
DOI
|
4 |
N. Paramanandham and K. Rajendiran, "Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications," Infrared Physics & Technology, vol. 88, pp. 13-22, 2018.
DOI
|
5 |
F. V. Moghadam and H. R. Shahdoosti, "A new multifocus image fusion method using contourlet transform," 2017.
|
6 |
W. Kong, "Technique for gray-scale visual light and infrared image fusion based on non-subsampled shearlet transform," Infrared Physics & Technology, vol. 63, no. 11, pp. 110-118, 2014.
DOI
|
7 |
K. Peter, "Model fitting and robust estimation source code for matlab,".
|
8 |
W. G. Wan, Y. Yang, H. J. Lee, "Practical remote sensing image fusion method based on guided filter and improved SML in the NSST domain," Signal, Image and Video Processing, vol. 12, no. 5, pp. 959-966, 2018.
DOI
|
9 |
X. Jin, G. Chen, J. Hou, "Multimodal sensor medical image fusion based on nonsubsampled shearlet transform and S-PCNNs in HSV space," Signal Processing, vol. 153, pp. 379-395, 2018.
DOI
|
10 |
J. Yang and J. Yang, "Multi-Channel Gabor Filter Design for Finger-Vein Image Enhancement," in Proc. of the fifth Inter. Conf. on Image and Graphics, pp. 87-91, 2009.
|
11 |
J. Yang, Y. Shi and J. Yang, "Personal identification based on finger-vein features," Computers in Human Behavior, vol. 27, no. 5, pp. 1565-1570, 2011.
DOI
|
12 |
X. Xu, D. Shan, G. Wang and X. Jiang, " Multimodal medical image fusion using pcnn optimized by the qpso algorithm," Applied Soft Computing, vol. 46, pp. 588-595, 2016.
DOI
|
13 |
L. Tang, J. Qian, L. Li, J. Hu and X. Wu, "Multimodal medical image fusion based on discrete tchebichef moments and pulse coupled neural network," International Journal of Imaging Systems & Technology, vol. 27, no. 1, pp. 57-65, 2017.
DOI
|
14 |
Weiwei Kong, Longjun Zhang, Yang Lei, "Novel fusion method for visible light and infrared images based on nsst-sf-pcnn," Infrared Physics & Technology, vol. 65, no. 7, pp. 103-112, 2014.
DOI
|
15 |
M. A. Kashiha, C. Bahr, S. Ott, C. Moons, T. A. Niewold and F. Tuyttens, "Automatic monitoring of pig activity using image analysis," Advanced Concepts for Intelligent Vision Systems. Springer International Publishing, 2013.
|
16 |
D. Stajnko, M. Brus and M. Ho Evar, "Estimation of bull live weight through thermographically measured body dimensions," Computers and Electronics in Agriculture, vol. 61, no. 2, pp. 233-240, 2008.
DOI
|
17 |
X. Bai, F. Zhou and B. Xue, "Fusion of infrared and visual images through region extraction by using mult-scale center-surround top-hat transform," Optics Express, vol. 19, no. 9, pp. 8444-8457, 2011.
DOI
|
18 |
F. R. Caldara, L. S. Dos Santos, S. T. Machado, M. Moi, de Alencar Nääs, Irenilza, and L. Foppa, "Piglets' surface temperature change at different weights at birth," Asian-Australasian journal of animal sciences, vol. 27, no. 3, pp. 431-438, 2014.
DOI
|
19 |
M. Alsaaod, C. Syring, J. Dietrich, M. G. Doherr, T. Gujan and A. Steiner, "A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows," The Veterinary Journal, vol. 199, no. 2, pp. 281-285, 2014.
DOI
|
20 |
K. Kawasue, K. D. Win, K. Yoshida and T. Tokunaga, "Black cattle body shape and temperature measurement using thermography and kinect sensor," Artificial Life and Robotics, vol. 22, pp. 464-470, 2017.
DOI
|
21 |
G. Bhatnagar, Q. M. J. Wu and Z. Liu, "A new contrast based multimodal medical image fusion framework," Neurocomputing, vol. 157, pp. 143-152, 2015.
DOI
|
22 |
C. Siewert, D. Hoeltig, C. Brauer, "Medial infrared imaging of the porcine thorax for diagnosis of lung pathologies," in Proc. of the 21st Int. Pig Veterinary Society Congress, Vol. II, Vancouver, pp. 663, 2010.
|
23 |
W. Ye and H. Xin, "Thermographical quantification of physiological and behavioral responses of group-housed young pigs," Transactions of the ASAE, vol. 43, no. 6, pp. 1843-1851, 2000.
DOI
|
24 |
T. S. Kammersgaard, J. Malmkvist, L. J. Pedersen, "Infrared thermography-a non-invasive tool to evaluate thermal status of neonatal pigs based on surface temperature," Animal, vol. 7, no. 12, pp. 2026-2034, 2013.
DOI
|
25 |
E. Vakaimalar, K. Mala and B. R. Suresh, "Multifocus image fusion scheme based on discrete cosine transform and spatial frequency," Multimedia Tools and Applications, 78, 17573-17587, 2019.
DOI
|
26 |
X. Jin, Q. Jiang, S. Yao, D. Zhou, R. Nie and S. J. Lee, "Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain," Infrared Physics & Technology, vol. 88, pp. 1-12, 2018.
DOI
|
27 |
L. I. He, L. Lei, Y. Chao and H. Wei, "An improved fusion algorithm for infrared and visible images based on multi-scale transform," Semiconductor Optoelectronics, vol. 74, pp. 28-37, 2016.
|
28 |
L. Wang, B. Li and L. F. Tian, "Eggdd: an explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain," Information Fusion, vol. 19, no. 11, pp. 29-37, 2014.
DOI
|
29 |
Q. Zhang and B. L. Guo, "Multifocus image fusion using the nonsubsampled contourlet transform," Signal Processing, vol. 89, no. 7, pp. 1334-1346, 2009.
DOI
|
30 |
T. Xiang, L. Yan and R. Gao, "A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking pcnn in nsct domain," Infrared Physics & Technology, vol. 69, pp. 53-61, 2015.
DOI
|
31 |
Bai and Xiangzhi, "Infrared and visual image fusion through feature extraction by morphological sequential toggle operator," Infrared Physics & Technology, vol. 71, pp. 77-86, 2015.
DOI
|
32 |
Y. Ma, J. Chen, C. Chen, F. Fan and J. Ma, "Infrared and visible image fusion using total variation model," Neurocomputing, vol. 202, pp. 12-19, 2016.
DOI
|
33 |
Z. Huang, M. Ding and X. Zhang, "Medical image fusion based on non-subsampled shearlet transform and spiking cortical model," Journal of Medical Imaging & Health Informatics, vol. 7, no. 1, pp. 229-234, 2017.
DOI
|
34 |
Y. Huang, D. Bi and D. Wu, "Infrared and visible image fusion based on different constraints in the non-subsampled shearlet transform domain," Sensors, vol. 18, no. 4, pp. 1169, 2018.
DOI
|
35 |
G. Yang, C. Ikuta, S. Zhang, Y. Uwate, Y. Nishio and Z. Lu, "A novel image fusion algorithm using an nsct and a pcnn with digital filtering," International Journal of Image & Data Fusion, vol. 9, pp. 82-94, 2018.
DOI
|
36 |
B. Cheng, L. Jin and G. Li, "A novel fusion framework of visible light and infrared images based on singular value decomposition and adaptive dual-pcnn in nsst domain," Infrared Physics & Technology, vol. 91, pp. 153-163, 2018.
DOI
|
37 |
Y. Chen and N. Sang, "Attention-based hierarchical fusion of visible and infrared images," Optik - International Journal for Light and Electron Optics, vol. 126, no. 23, pp. 4243-4248, 2015.
DOI
|
38 |
J. Ma, C. Chen, C. Li and J. Huang, "Infrared and visible image fusion via gradient transfer and total variation minimization," Information Fusion, vol. 31, pp. 100-109, 2016.
DOI
|
39 |
W. Kong, Y. Lei, M. Ren, "Fusion method for infrared and visible images based on improved quantum theory model," Neurocomputing, vol. 212, pp. 12-21, 2016.
DOI
|
40 |
K. Ma, K. Zeng and Z. Wang, "Perceptual quality assessment for multi-exposure image fusion," IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3345-3356, 2015.
DOI
|
41 |
S. M. Nemalidinne and D. Gupta, "Nonsubsampled contourlet domain visible and infrared image fusion framework for fire detection using pulse coupled neural network and spatial fuzzy clustering," Fire Safety Journal, vol. 101, pp. 84-101, 2018.
DOI
|