Identification and replacement of defective pixel based on Matlab for IR sensor

Minghui YANG, Sihai CHEN, Xin WU, Wen FU, Zhangli HUANG

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PDF(172 KB)
Front. Optoelectron. ›› 2011, Vol. 4 ›› Issue (4) : 434-437. DOI: 10.1007/s12200-011-0177-2
RESEARCH ARTICLE
RESEARCH ARTICLE

Identification and replacement of defective pixel based on Matlab for IR sensor

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Abstract

Infrared focal plane arrays (IRFPAs) usually contain many defective pixels. These defective pixels have to be corrected because those can significantly impair the performance of infrared image of IRFPAs. As is known to all, infrared image acquisition and analysis based on Matlab can be helpful to identify and correct defective pixels. In this paper, we proposed a novel method to identify and correct defective pixels. In the phase of identification, the defective pixels could be identified by the algorithms combined with median filtering algorithm and improved standard deviation algorithm. In the phase of correction, proportion-spatial defective pixel replacement (PSDPR) algorithm was introduced to replace the defective pixels, and this method reduced the difficulty of replacement originating from the clustering phenomenon of defective pixels. In addition, an experiment of verification was done, and showed the proposed scheme worked effectively.

Keywords

infrared focal plane arrays (IRFPAs) / infrared image / median filtering algorithm / improved standard deviation algorithm

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Minghui YANG, Sihai CHEN, Xin WU, Wen FU, Zhangli HUANG. Identification and replacement of defective pixel based on Matlab for IR sensor. Front Optoelec Chin, 2011, 4(4): 434‒437 https://doi.org/10.1007/s12200-011-0177-2

References

[1]
Tajbakhsh T. Efficient defect pixel cluster detection and correction for Bayer CFA image sequences. In: Proceedings of SPIE, 2011, 7876: 78760I
[2]
López-Alonso J M, Alda J. Bad pixel identification by means of principal components analysis. Optical Engineering, 2002, 41(9): 2152–2157
[3]
Wang B J, Liu S Q, Li Q, Lei R. Blind-pixel correction algorithm for an infrared focal plane array based on moving-scene analysis. Optical Engineering, 2006, 45(3): 036401
[4]
Zhang K, Zhao G F, Cui R Q, Yuan Q J. Method of improving bad pixel detection precision of IRFPA. Infrared and Laser Engineering, 2007, 36(4): 453–456
[5]
Fischer A D,Downes T V, Leather R. Median spectral-spatial bad pixel identification and replacement for hyperspectral SWIR sensors. In: Shen S S, Lewis P E, eds. Proceedings of SPIE, 2011, 6565: 65651E
[6]
Ghosh S, Marshall I, Freitas A A. Autonomously detecting the defective pixels in an imaging sensor array using a robust statistical technique. In: Proceedings of SPIE-IS & T, 2008, 6808: 680813
[7]
Mao J X, Wang Y F. Statistical analysis of defective pixels for IRFPA detector using MATLAB. Infrared, 2009, 30(3): 43–45
[8]
Zhang S Q, Karim M A. A new impulse detector for switching median filters. IEEE Signal Processing Letters, 2002, 9(11): 360–363
[9]
Meng X L, Zhang W, Cong M Y, Cao Y M, Bao W Z. Bad pixel replacement based on spatial statistics for IR sensor. In: Proceedings of SPIE, 2010, 7658: 76582N
[10]
Huang X, Zhang J Q, Liu D L. Algorithm of blind pixels compensation for adaptive detection and infrared image. Infrared and Laser Engineering, 2011, 40(7): 370–376
[11]
Demirhan M, Özpinar A, Özdamar L. Performance evaluation of spatial interpolation methods in the presence of noise. International Journal of Remote Sensing, 2003, 24(6): 1237–1258
[12]
An J, Lee W, Kim J. Adaptive detection and concealment algorithm of defective pixel. In: IEEE workshop on Signal Processing Systems, 2007: 651–656
[13]
Tanbakuchi A A, van der Sijde A, Dillen B, Theuwissen A J P, de Haan W. Adaptive pixel defect correction. In: Proceedings of SPIE, 2003, 5017: 360–370
[14]
Rummelt N I, Cicchi T, Curzan J P. A combined non-uniformity and bad pixel correction method for superpixelated infrared imagery. In: Proceedings of SPIE, 2006, 6206: 62060V

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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