[Table of Contents]

Plasma and Fusion Research

Volume 7, 2404120 (2012)

Regular Articles


A New De-Noising Method of Laser-Produced Plasma Penumbral Images by Principal Component Analysis
Shinya NOZAKI, Atsushi KINJO, Shinsuke FUJIOKA1), Rumiko AZUMA2), Yen-Wei CHEN3) and Yoshinori NAMIHIRA
University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
1)
Osaka University, Suita, Osaka 565-0871, Japan
2)
Aoyama University, Sagamihara, Kanagawa 252-5258, Japan
3)
Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan
(Received 29 November 2011 / Accepted 29 May 2012 / Published 13 September 2012)

Abstract

Penumbral imaging technique can be applied to highly penetrating radiations such that of as neutrons. In penumbral imaging, the source image can be recovered from its penumbral image by deconvolution. The method is an efficient imaging technique for fast ignition research. However, the γ rays produced by the fast-heating laser pollute the penumbral image as noise. Conventional deconvolution methods like the Wiener filter cannot obtain a clear reconstructed image from noisy penumbral image. In this paper, we propose a new reconstruction method by principal component analysis (PCA). The method can efficiently remove the noise by “training” images obtained from other experiments. We used the (2D)2 PCA method as a noise reduction method, which is one of the PCA methods. The efficacy of the proposed method is demonstrated by computer simulation.


Keywords

penumbral imaging, deconvolution, Wiener filter, fast ignition, principal component analysis

DOI: 10.1585/pfr.7.2404120


References

  • [1] K.A. Nugent and L. Davis, Opt. Commun. 49, 393 (1984).
  • [2] Y.-W. Chen, K. Otsuki, Z. Nakao and R. Kodama, Rev. Sci. Instrum. 69, 1966 (1998).
  • [3] Y.-W. Chen et al., Opt. Commun. 73, 337 (1989).
  • [4] S. Nozaki, Y.-W. Chen, Z. Nakao, R. Kodama and H. Shiraga, Rev. Sci. Instrum. 74, 2240 (2003).
  • [5] Y.-W. Chen, H. Yamamoto and S. Nozaki, Rev. Sci. Instrum. 75, 4017 (2004).
  • [6] T. Ueda et al., Rev. Sci. Instrum. 81, 073505 (2010).
  • [7] R. Kodama et al., Nature 418, 933 (2002).
  • [8] J. Yang et al., IEEE Trans. Pattern Anal. Mach. Intell. 26, 131 (2004).
  • [9] D. Zhang and Z.-H. Zhou, Neurocomputing 69, 224 (2005).

This paper may be cited as follows:

Shinya NOZAKI, Atsushi KINJO, Shinsuke FUJIOKA, Rumiko AZUMA, Yen-Wei CHEN and Yoshinori NAMIHIRA, Plasma Fusion Res. 7, 2404120 (2012).