Volume 43 Issue 2
Mar.  2014
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Yan Fei, Hou Qingyu. Algorithm of blind-pixel detection based on multi-statistical characteristic abnormity[J]. Infrared and Laser Engineering, 2014, 43(2): 454-457.
Citation: Yan Fei, Hou Qingyu. Algorithm of blind-pixel detection based on multi-statistical characteristic abnormity[J]. Infrared and Laser Engineering, 2014, 43(2): 454-457.

Algorithm of blind-pixel detection based on multi-statistical characteristic abnormity

  • Received Date: 2013-06-10
  • Rev Recd Date: 2013-07-25
  • Publish Date: 2014-02-25
  • Aiming at the severe problems of system performance degradation that was caused by the blind pixels and the nonuniformity which exists in Infrared Focal Plane Array (IRFPA), multivariate normal distribution sequence noise model of IRFPA was set up firstly, and blind-pixel was regarded as abnormity pixel for the unconformiting mold statistical distribution characteristic and it was dissociating the multivariate normal distribution ellipsoid. Then the principal component was applied to sequence pattern, and the statistical distance and bisectrix spatial angle are regard as statistical criterion of abnormity pixels detection. Finally, to test and verify the performance of the method on taken full advantage of thermal infrared imager to do sequential multiple frames of noise data collection. The algorithm was applied to actual blind pixel detection of uncooled IRFPA and the validity of the algorithm was proved by the experimental result.
  • [1]
    [2] Xing Suxia, Zhang Junju, Chang Benkang, et al. Recent development and status of uncooled IR thermal imaging technology[J]. Infrared and Laser Engineering, 2004, 33(5): 441-444. (in Chinese)
    [3] 邢素霞,张俊举,常本康,等.非制冷红外热成像技术的发展与现状[J]. 红外与激光工程, 2004, 33(5): 441-444.
    [4] Li Xu, Yang Hu. Application of a nonuniformity correction algorithm for IRFPAs based on two points[J]. Infrared and Laser Engineering, 2008, 37(s2): 608-610. (in Chinese)
    [5] Zhang Ke, Zhao Guifang, Cui Ruiqing, et al. Method of improving bad pixel detection precision of IRFPA[J]. Infrared and Laser Engineering, 2007,36(4): 453-456. (in Chinese)
    [6]
    [7]
    [8] Zhou Huixin, Yin Shimin, Liu Shangqian, et al. Algorithm of blind pixels auto-searching and compensation for IRFPA[J]. Acta Photonica Sinica, 2004, 33(5): 598-600. (in Chinese)
    [9] 李旭, 杨虎. 基于两点的红外图像非均匀性校正算法应用[J]. 红外与激光工程, 2008, 37(s2): 608-610.
    [10] Lai Rui, Liu Shangqian,Zhou Huixin, et al. Blind-pixel detection for infrared focal plane arrays[J]. Semiconductor Optoelectronics, 2005, 26(3):199-201. (in Chinese)
    [11] D'Agostino J A, Webb C M. Three-dimensional analysis framework and measurement methodology for imaging system noise[C]//SPIE, 1991, 1488: 110-121.
    [12]
    [13]
    [14] Lopez-Alonso J M, Alda J, Bernabeu E. Principal-component characterization of noise for infrared images[J]. Applied Optics, 2002, 41(2): 320-331.
    [15] 张科, 赵桂芳, 崔瑞青, 等. 一种提高红外焦平面阵列盲元检测精度的方法[J]. 红外与激光工程, 2007, 36(4): 453-456.
    [16] Lopez-Alonso J M, Alda J. Bad pixel identification by means of principal components analysis[J]. Optical Engineering, 2002, 41(9): 2152-2157.
    [17]
    [18]
    [19] 周慧鑫, 殷世民, 刘上乾, 等.红外焦平面器件盲元检测及补偿算法[J]. 光子学报, 2004, 33(5): 598-600.
    [20]
    [21]
    [22]
    [23]
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Algorithm of blind-pixel detection based on multi-statistical characteristic abnormity

  • 1. Tianjing Bureau of Naval Equipment Ministry,Beijing 100000,China;
  • 2. Research Center for Space Optical Engineering,Harbin Institute of Technology,Harbin 150001,China

Abstract: Aiming at the severe problems of system performance degradation that was caused by the blind pixels and the nonuniformity which exists in Infrared Focal Plane Array (IRFPA), multivariate normal distribution sequence noise model of IRFPA was set up firstly, and blind-pixel was regarded as abnormity pixel for the unconformiting mold statistical distribution characteristic and it was dissociating the multivariate normal distribution ellipsoid. Then the principal component was applied to sequence pattern, and the statistical distance and bisectrix spatial angle are regard as statistical criterion of abnormity pixels detection. Finally, to test and verify the performance of the method on taken full advantage of thermal infrared imager to do sequential multiple frames of noise data collection. The algorithm was applied to actual blind pixel detection of uncooled IRFPA and the validity of the algorithm was proved by the experimental result.

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