Volume 47 Issue 6
Jul.  2018
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Wei Wei, Xiang Wei, Zhao Yaohong. An narcissus effect correction method based on spatial and time domain estimation[J]. Infrared and Laser Engineering, 2018, 47(6): 626003-0626003(8). doi: 10.3788/IRLA201847.0626003
Citation: Wei Wei, Xiang Wei, Zhao Yaohong. An narcissus effect correction method based on spatial and time domain estimation[J]. Infrared and Laser Engineering, 2018, 47(6): 626003-0626003(8). doi: 10.3788/IRLA201847.0626003

An narcissus effect correction method based on spatial and time domain estimation

doi: 10.3788/IRLA201847.0626003
  • Received Date: 2018-01-05
  • Rev Recd Date: 2018-02-03
  • Publish Date: 2018-06-25
  • Narcissus effect was an important factor that influence the imaging quality of the cooled infrared detector. Although it can be removed by non-uniform correction techniques, narcissus effect will reappear once the operating conditions have changed. Through analyzing the manifestation of narcissus effect, a correction algorithm based on adaptive spatial-temporal filtering was proposed. First, spatial domain estimation of Narcissus effect was captured by wavelet transform. Then, time domain estimation of Narcissus effect was gained by adaptive time domain low-pass filtering. Finally, the correction was applied by subtracting the estimated spatial-temporal noise from the original image. Experimental results on simulated and actual infrared image sequences have verified the effectiveness of the proposed algorithm.
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    [2] Howard J W, Abel I R. Narcissus:reflections on retroreflections in thermal imaging systems[J]. Applied Optics, 1982, 21(18):3393-3397.
    [3] Fan F, Ma Y, Huang J, et al. A combined temporal and spatial deghosting technique in scene based nonuniformity correction[J]. Infrared Physics Technology, 2015, 71:408-415.
    [4] Zuo C, Chen Q, Gu G, et al. Scene-based nonuniformity correction algorithm based on interframe registration[J]. Journal of the Optical Society of America a Optics Image Science Vision, 2011, 28(6):1164-1176.
    [5] Zuo C, Chen Q, Gu G, et al. Improved interframe registration based nonuniformity correction for focal plane arrays[J]. Infrared Physics Technology, 2012, 55(4):263-269.
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    [7] Zuo C, Chen Q, Gu G, et al. New temporal high-pass filter nonuniformity correction based on bilateral filter[J]. Laser Infrared, 2011, 18(2):197-202.
    [8] Li Z, Shen T, Lou S. Scene-based nonuniformity correction based on bilateral filter with reduced ghosting[J]. Infrared Physics Technology, 2016, 77:360-365.
    [9] Liu Zhixiang, Ma Dongmei, Hu Mingpeng, et al. Simulation analysis of the narcissus in the staring infrared imaging system[J]. Infrared and Laser Engineering, 2008, 37(4):702-705. (in Chinese)刘志祥, 马冬梅, 胡明鹏, 等. 凝视型红外成像系统中冷像的仿真分析[J]. 红外与激光工程, 2008, 37(4):702-705.
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An narcissus effect correction method based on spatial and time domain estimation

doi: 10.3788/IRLA201847.0626003
  • 1. Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China;
  • 2. University of Chinese Academy of Sciences,Beijing 100049,China;
  • 3. Key Laboratory of Opto-Electronic Information Processing,Chinese Academy of Sciences,Shenyang 110016,China;
  • 4. The Key Lab of Image Understanding and Computer Vision,Liaoning Province,Shenyang 110016,China

Abstract: Narcissus effect was an important factor that influence the imaging quality of the cooled infrared detector. Although it can be removed by non-uniform correction techniques, narcissus effect will reappear once the operating conditions have changed. Through analyzing the manifestation of narcissus effect, a correction algorithm based on adaptive spatial-temporal filtering was proposed. First, spatial domain estimation of Narcissus effect was captured by wavelet transform. Then, time domain estimation of Narcissus effect was gained by adaptive time domain low-pass filtering. Finally, the correction was applied by subtracting the estimated spatial-temporal noise from the original image. Experimental results on simulated and actual infrared image sequences have verified the effectiveness of the proposed algorithm.

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