Fusion of infrared and visible images based on focus measure operators in the curvelet domain

Applied Optics

Volumn 51, Issue 12, 2012, Pages 1910-1921

  Shao, Zhenfeng ^a   Liu, Jun ^a   Cheng, Qimin ^b  

^a WUHAN UNIVERSITY   (China)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ENHANCEMENT; INFRARED DETECTORS; INFRARED IMAGING; INVERSE PROBLEMS;

CORRELATION COEFFICIENT; FAST DISCRETE CURVELET TRANSFORMS; FOCUS MEASURE OPERATOR; HIGH-FREQUENCY INFORMATIONS; IMAGE FUSION METHODS; INFRARED AND VISIBLE IMAGE; LOW FREQUENCY FEATURES; PHYSICAL CHARACTERISTICS;

IMAGE FUSION;

EID: 84860178811     PISSN: 1559128X     EISSN: 15394522     Source Type: Journal    
DOI: 10.1364/AO.51.001910     Document Type: Article

References (21)

1. F. F. Zhou, W. D. Chen, and L. F. Li, "Fusion of IR and visible images using region growing," J. Appl. Opt. 28, 737-741 (2007) (in Chinese).
2. A. Apatean, C. Rusu, A. Rogozan, and A. Bensrhair, "Visibleinfrared fusion in the frame of an obstacle recognition system," in IEEE International Conference on Automation, Quality and Testing, Robotics (IEEE, 2010), pp. 1-6.
3. X. H. Yang, H. Y. Jin, and L. C. Jiao, "Adaptive image fusion algorithm for infrared and visible light images based on DT-CWT," J. Infrared Millim. Waves 26, 419-424 (2007).
4. H. M. Wang, K. Zhang, and Y. J. Li, "Image fusion algorithm based on wavelet transform," Infrared Laser Eng. 34, 328-332 (2005) (in Chinese).
5. S. Firooz, "Comparative image fusion analysis," in IEEE Proceedings of the Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 1-8.
6. G. Pajares and J. M. de la Cruz, "A wavelet-based image fusion tutorial," Pattern Recogn. 37, 1855-1872 (2004).
7. R. Minhas, A. A. Mohammed, and Q. M. J. Wu, "Shape from focus using fast discrete curvelet transform," Pattern Recogn. 44, 839-853 (2011).
8. S. Li and B. Yang, "Multifocus image fusion by combining curvelet and wavelet transform," Pattern Recogn. Lett. 29, 1295-1301 (2008).
9. X. B. Qu, J. W. Yan, and G. D. Yang, "Multifocus image fusion method of sharp frequency localized contourlet transform domain based on sum-modified-Laplacian," Opt. Precision Eng. 17, 1203-1212 (2009).
10. E. J. Candès and D. L. Donoho, "New tight frames of curvelets and optimal representations of objects with C2 singularities," Commun. Pure Appl. Math. 57, 219-266 (2004).]
11. E. J. Candès, L. Demanet, andD. L. Donoho, "Fast discrete curvelet transforms," Multiscale Model. Simul. 5, 861-899 (2006).
12. W.HuangandZ. L.Jing, "Evaluationoffocusmeasuresinmultifocus image fusion," Pattern Recogn. Lett. 28, 493-500 (2007).
13. R. Minhas, A. A. Mohammed, and Q. M. J. Wu, "An efficient algorithm for focus measure computation in constant time," IEEE Trans. Circuits Syst. Video Technol. 22: 152-156 (2012).
14. R. Minhas, A. A. Mohammed, Q. M. J. Wu, and M. A. Sid- Ahmed, "3D shape from focus and depth map computation using steerable filters," Lect. Notes Comput. Sci. 5627, 573-583 (2009).
15. M. Muhammad and T. S. Choi, "Sampling for shape from focus in optical microscopy," IEEE Trans. Pattern Anal. Machine Intell. 99, 1-12 (2011).
16. V. Aslantas and R. Kurban, "A comparison of criterion functions for fusion of multi-focus noisy images," Opt. Commun. 282, 3231-3242 (2009).
17. S. K. Nayar and Y. Nakagawa, "Shape from focus," IEEE Trans. Pattern Anal. Machine Intell. 16, 824-831 (1994).
18. Z. Wang and A. C. Bovik, "A universal image quality index," IEEE Signal Process Lett. 9, 81-84 (2002).
19. G. X. Liu, S. G. Zhao, and W. H. Yang, "Multi-sensor image fusion scheme based on gradient pyramid decomposition," J. Optoelectron. Laser 12, 293-296 (2001) (in Chinese).
20. J. Liu and Z. F. Shao, "Feature-based remote sensing image fusion quality metrics using structure similarity," Acta Photon. Sin. 40, 126-131 (2011).
21. M. Welling, "Robust higher order statistics," in Proceedings of 10th International Workshop on Artificial Intelligence and Statistics (2005), pp. 405-412.