Optical Review

, Volume 17, Issue 1, pp 24–29

Space low-pass and temporal high-pass nonuniformity correction algorithm

Regular Papers

Abstract

Nowadays, almost all scene-based nonuniformity correction (NUC) algorithms have the same shortcoming: a low convergence speed. This shortcoming produces ghosting artifacts. In this paper, we will start by discussing the traditional temporal high-pass NUC algorithm, and then combine the space frequency and temporal frequency. This combination will produce a new algorithm called the space low-pass and temporal high-pass NUC algorithm. The kernel idea of this algorithm is to eliminate the nonuniformity’s high-space-frequency part and retain the nonuniformity’s low-space-frequency part. Moreover, the high-space-frequency part’s processing is controllable, which markedly increases convergence speed. These features make our algorithm’s convergence speed so high that processed images have almost no ghosting artifacts.

Keywords

scene-based nonuniformity correction ghosting artifacts temporal high-pass space low-pass convergence speed 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1).
    Y. Jian, S. Ruan, H. Zhou, and C. Liu: Proc. IEEE 6th World Congre. Intelligent Control and Automation, 2006, p. 10328.Google Scholar
  2. 2).
    A. F. Milton, F. R. Barone, and M. R. Kruer: Opt. Eng. 24 (1985) 855.Google Scholar
  3. 3).
    J. M. Mooney, F. D. Shepherd, W. S. Ewing, J. E. Murguia, and J. Silverman: Opt. Eng. 28 (1989) 1151.ADSGoogle Scholar
  4. 4).
    M. Schulz and L. Caldwell: Proc. SPIE 2470 (1995) 200.CrossRefADSGoogle Scholar
  5. 5).
    S. Ullman and G. Schechtman: Proc. R. Soc. London, Ser. B 216 (1982) 299.CrossRefADSGoogle Scholar
  6. 6).
    D. A. Scribner, K. A. Sarkady, J. T. Caulfield, M. R. Kruer, G. Katz, and C. J. Gridly: Proc. SPIE 1308 (1990) 224.CrossRefADSGoogle Scholar
  7. 7).
    D. A. Scribner, K. A. Sarkady, and J. T. Caulfield: Proc. IEEE Int. Conf. Neural Networks, 1993, p. 1955.Google Scholar
  8. 8).
    J. G. Harris and Y. M. Chiang: IEEE Trans. Image Process. 8 (1999) 1148.CrossRefADSGoogle Scholar
  9. 9).
    R. Charnigo, J. Sun, and R. Muzic, Jr.: IEEE Trans. Image Process. 15 (2006) 666.CrossRefMathSciNetADSGoogle Scholar

Copyright information

© The Optical Society of Japan 2010

Authors and Affiliations

  1. 1.440 Lab, EEOTNanjing University of Science and TechnologyNanjing, Jiangsu ProvinceChina

Personalised recommendations