Pixel-Level fusion for infrared and visible acquisitions

International Journal of Optomechatronics

Volumn 3, Issue 1, 2009, Pages 41-53

  Zhou, Yi ^a   Omar, Mohammed ^b  

^a AMRL   (United States)

^b CLEMSON UNIVERSITY   (United States)

Author keywords

Average thresholding; Image fusion; Night vision; Pixel level fusion; Vehicle tracking

Indexed keywords

ADAPTIVE ALGORITHMS; IMAGE FUSION; PEDESTRIAN SAFETY; ROADS AND STREETS; VISION;

ADAPTIVE WEIGHTING; AVERAGE THRESHOLDING; DATA POINTS; FEATURE LEVELS; GAUSSIAN SMOOTHING; LONG WAVE INFRARED; LOW LIGHTS; NIGHT VISION; ORIENTATION PREDICTIONS; PASSIVE DISPLAYS; PIXEL-LEVEL FUSION; POST-PROCESSING; SHAPE RETRIEVALS; THERMAL IMAGERIES; VEHICLE TRACKING; VISION MODULES;

PIXELS;

EID: 61349151849     PISSN: 15599612     EISSN: 15599620     Source Type: Journal    
DOI: 10.1080/15599610902717835     Document Type: Article

References (17)

1. Zhang, Z. and Blum, R. S. (1999) A Categorization and Study of Multiscale-decomposition-based Image Fusion Schemes. Proceedings of the IEEE, pp. 1315-1328.
2. Brown, L. G. (1992) A survey of image registration techniques. ACM Computing Surveys, 24:4, pp. 325-376.
3. David, O., Kopeika, N. S. and Weizer, B. (2006) Range gated active night vision system for automobiles. Journal of Applied Optics, 45, pp. 7248-7254.
4. Heather, J. P. and Smith, M. L. (2005) 1, pp. 8-14.
5. Hong, G. and Zhang, Y. (2003) High resolution image fusion based on Wavelet and IHS transformations. pp. 99-104.
6. Kaellhammer, J. E. (2006) The road ahead for car night-vision. Nature Photonics, 5, pp. 12-13.
7. Klemm, R. (2004)
8. Krebs, W. K. and Scribner, D. A. (2001) Comparing behavioral receiver operating characteristic curves to multidimensional matched filters. Optical Engineering, 40:9, pp. 1818-1826.
9. Lallier, F. and Farooq, M. (2000) A real time pixel-level based image fusion via adaptive weight averaging. pp. 3-2.
10. Lanir, Y. (2005)
11. Lee, T. S., Shie, J. S. and Li, Hung-Ti (1998) Application studies of a simulated low density room-temperature IRFPA. Thermosense XX, 3361, pp. 26-34.
12. Li, H., Manjunath, B. S. and Mitra, S. K. (1995) Multisensor image fusion using the wavelet transform. Graph. Models Image Process, 57:3, pp. 235-245.
13. Luo, R. and Kay, M. (1992) Data Fusion in Robotics and Machine Intelligence, Academic Press, San Diego
14. Omar, M. and Zhou, Y. (2007) Pedestrian tracking routine for passive automotive night vision systems. Sensor Review, 27:4, pp. 310-316.
15. Pajares, G. and Manuel de la Cruz, J. (2004) A wavelet-based image fusion tutorial. Pattern Recognition, 37, pp. 1855-1872.
16. Waxman, A. M., Aguilar, M., Baxter, R. A., Fay, D. A. and Ireland, D. B. (1998) Opponent-color fusion of multi-sensor imagery: Visible, IR and SAR.1, pp. 43-61.
17. Zhang, Z. and Blum, R. S. (1999) A Categorization and Study of Multiscale-decomposition-based Image Fusion Schemes. Proceedings of the IEEE, pp. 1315-1328.