Classified Image Enhancement of IRST Based on Loaded Location in Ship and AOS

함정 탑재 위치 및 AOS에 기반한 적외선탐지추적 장비의 영역별 영상 향상

  • Published : 2007.09.30

Abstract

In this paper, I propose a method which can enhance the visual quality of IRST images based on a loaded location in ship and an AOS. The IRST adjusts an AOS to detect targets with various altitudes because of its narrow vertical field of view and offers various functions to enhance images with its low contrast. In the proposed method, images are divided into two regions of sea and sky on the basis of the horizon after establishing relation between an AOS and a horizon location within an image. As a result, image enhancement of the proposed method is performed adaptively according to the divided region while that of conventional method is performed for entire image without the region division. Simulation results show that the proposed method represents higher visibility compared with conventional one.

Keywords

References

  1. Scott, R. and Janssen, J., 'IRSTs see their second coming', Jane's Navy International, Jane's Publishing Company Ltd., pp. 26-28, 1996. 12
  2. 'EL-OP revives IRST development', Jane's Navy International, Jane's Publishing Company Ltd., p. 6, 1996. 3
  3. Peruzzi L,, 'Italian navy prepares for Galileo Avionica's SASS IRST', Jane's Navy International, Jane's Publishing Company Ltd., 2006. 12
  4. Scott, R., 'UK develops advanced infra-red search and track demonstrator', Jane's Defence Weekly, Jane's Publishing Company Ltd., pp.28-29, 2003. 10. 29
  5. Shao, M., Liu, G., Liu, X. and Zhu, D., 'A new approach for infrared image contrast enhancement', Proc. of SPIE, Vol. 6150, No.1, pp. 615009-1-615009-6, 2006. 5.
  6. Gonzalez, R. C. and Woods, R. E., Digital Image Processing 2nd Edition, Prentice Hall Inc., pp. 75-219, 1994
  7. Ralph, H. and Michael, B., 'Model-based image enhancement of far infrared images', IEEE Trans. on Pattern analysis and machine intelligence. Vol. 19, No. 4, pp. 410-415, 1997. 4 https://doi.org/10.1109/34.588029
  8. Nie, S., Feng, S., Feng L., Wang, M., 'Novel algorithm for infrared image enhancement', Proc. of SPIE, Vol. 5640, pp.151-156, 2005. 1
  9. Wang, B. J., Liu, S. Q., Li, Q. and Zhou, H. X., 'A real time contrast enhancement algorithm for infrared images based on plateau histogram', J. Infrared Physics & Technology, Vol. 48, No. 1, pp. 77-82, 2006. 4 https://doi.org/10.1016/j.infrared.2005.04.008
  10. Markham, K. C., 'Comparison of segmentation process for object acquisition in infrared images', Proc. of IEE, Vol. 136, No. 1, pp.13-21, 1989. 2
  11. Neves, S. R., Silva, E. A. B. and Mendonca, G. V., 'Wavelet-watershed automatic infrared image segmentation method', Electronics Letters, Vol. 39, No. 12, pp. 903-904, 2003. 6 https://doi.org/10.1049/el:20030617
  12. Wu, J., Li, J., LIU, J. and TIAN, J., 'Infrared image segmentation via fast fuzzy C-means with spatial information', Proc. of IEEE, pp.742-745, 2004. 8
  13. Campana, S. B., The Infrared and Electro-Optical Systems Handbook Volume 5, Infrared Information Analysis Center and SPIE Optical Engineering Press, pp. 107-109, 1993