Abstract

The spatial fixed-pattern noise (FPN) inherently generated in infrared (IR) imaging systems compromises severely the quality of the acquired imagery, even making such images inappropriate for some applications. The FPN refers to the inability of the photodetectors in the focal-plane array to render a uniform output image when a uniform-intensity scene is being imaged. We present a noise-cancellation-based algorithm that compensates for the additive component of the FPN. The proposed method relies on the assumption that a source of noise correlated to the additive FPN is available to the IR camera. An important feature of the algorithm is that all the calculations are reduced to a simple equation, which allows for the bias compensation of the raw imagery. The algorithm performance is tested using real IR image sequences and is compared to some classical methodologies.

© 2008 Optical Society of America

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References

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  1. U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
    [CrossRef]
  2. P. M. Narendra and N. A. Foss, “Shutterless fixed pattern noise correction for infrared imaging arrays,” Proc. SPIE 282, 44-51 (1981).
  3. J. G. Harris and Y.-M. Chiang, “An analog implementation of the constant average statistics constraint for sensor calibration,” in Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and T. Petsche, eds. (MIT, 1997) Vol. 9, p. 699.
  4. B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
    [CrossRef]
  5. J. G. Harris and Y. M. Chiang, “Nonuniformity correction using the constant-statistics constraint: analog and digital implementations,” Proc. SPIE 3061, 895-905 (1997).
    [CrossRef]
  6. S. N. Torres and M. M. Hayat, “Kalman filtering for adaptive nonuniformity correction in infrared focal plane arrays,” J. Opt. Soc. Am. A 20, 470-480 (2003).
    [CrossRef]
  7. M. M. Hayat, S. N. Torres, E. Armstrong, S. C. Cain, and B. Yasuda, “Statistical algorithm for nonuniformity correction in focal-plane arrays,” Appl. Opt. 38, 772-780 (1999).
    [CrossRef]
  8. J. G. Harris and Y.-M. Chiang, “Nonuniformity correction of infrared image sequences using the constant-statistics constraint,” IEEE Trans. Image Process. 8, 1148-1151 (1999).
    [CrossRef]

2004 (1)

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

2003 (1)

1999 (2)

J. G. Harris and Y.-M. Chiang, “Nonuniformity correction of infrared image sequences using the constant-statistics constraint,” IEEE Trans. Image Process. 8, 1148-1151 (1999).
[CrossRef]

M. M. Hayat, S. N. Torres, E. Armstrong, S. C. Cain, and B. Yasuda, “Statistical algorithm for nonuniformity correction in focal-plane arrays,” Appl. Opt. 38, 772-780 (1999).
[CrossRef]

1997 (2)

J. G. Harris and Y. M. Chiang, “Nonuniformity correction using the constant-statistics constraint: analog and digital implementations,” Proc. SPIE 3061, 895-905 (1997).
[CrossRef]

J. G. Harris and Y.-M. Chiang, “An analog implementation of the constant average statistics constraint for sensor calibration,” in Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and T. Petsche, eds. (MIT, 1997) Vol. 9, p. 699.

1981 (1)

P. M. Narendra and N. A. Foss, “Shutterless fixed pattern noise correction for infrared imaging arrays,” Proc. SPIE 282, 44-51 (1981).

1975 (1)

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Armstrong, E.

Cain, S. C.

Chiang, Y. M.

J. G. Harris and Y. M. Chiang, “Nonuniformity correction using the constant-statistics constraint: analog and digital implementations,” Proc. SPIE 3061, 895-905 (1997).
[CrossRef]

Chiang, Y.-M.

J. G. Harris and Y.-M. Chiang, “Nonuniformity correction of infrared image sequences using the constant-statistics constraint,” IEEE Trans. Image Process. 8, 1148-1151 (1999).
[CrossRef]

J. G. Harris and Y.-M. Chiang, “An analog implementation of the constant average statistics constraint for sensor calibration,” in Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and T. Petsche, eds. (MIT, 1997) Vol. 9, p. 699.

Dong, E.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Foss, N. A.

P. M. Narendra and N. A. Foss, “Shutterless fixed pattern noise correction for infrared imaging arrays,” Proc. SPIE 282, 44-51 (1981).

Glover, J. R.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Goodlin, R. C.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Hardie, R. C.

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

Harris, J. G.

J. G. Harris and Y.-M. Chiang, “Nonuniformity correction of infrared image sequences using the constant-statistics constraint,” IEEE Trans. Image Process. 8, 1148-1151 (1999).
[CrossRef]

J. G. Harris and Y.-M. Chiang, “An analog implementation of the constant average statistics constraint for sensor calibration,” in Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and T. Petsche, eds. (MIT, 1997) Vol. 9, p. 699.

J. G. Harris and Y. M. Chiang, “Nonuniformity correction using the constant-statistics constraint: analog and digital implementations,” Proc. SPIE 3061, 895-905 (1997).
[CrossRef]

Hayat, M. M.

Hearn, R. H.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Kaunitz, J.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

McCool, J. M.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Narendra, P. M.

P. M. Narendra and N. A. Foss, “Shutterless fixed pattern noise correction for infrared imaging arrays,” Proc. SPIE 282, 44-51 (1981).

Ratliff, B. M.

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

Sakoglu, U.

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

Torres, S. N.

Tyo, J. S.

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

Widrow, B.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Williams, C. S.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Yasuda, B.

Zeidler, J. R.

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Appl. Opt. (1)

IEEE Trans. Image Process. (1)

J. G. Harris and Y.-M. Chiang, “Nonuniformity correction of infrared image sequences using the constant-statistics constraint,” IEEE Trans. Image Process. 8, 1148-1151 (1999).
[CrossRef]

J. Opt. Soc. Am. A (1)

Proc. IEEE (1)

B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. IEEE 63, 1692-1716 (1975).
[CrossRef]

Proc. SPIE (3)

J. G. Harris and Y. M. Chiang, “Nonuniformity correction using the constant-statistics constraint: analog and digital implementations,” Proc. SPIE 3061, 895-905 (1997).
[CrossRef]

U. Sakoglu, R. C. Hardie, M. M. Hayat, B. M. Ratliff, and J. S. Tyo, “An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence,” Proc. SPIE 5558, 69-79 (2004).
[CrossRef]

P. M. Narendra and N. A. Foss, “Shutterless fixed pattern noise correction for infrared imaging arrays,” Proc. SPIE 282, 44-51 (1981).

Other (1)

J. G. Harris and Y.-M. Chiang, “An analog implementation of the constant average statistics constraint for sensor calibration,” in Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and T. Petsche, eds. (MIT, 1997) Vol. 9, p. 699.

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Figures (4)

Fig. 1
Fig. 1

Block diagram of the NC-based algorithm.

Fig. 2
Fig. 2

Average RMSE per pixel as a function of (a) both the number of filter coefficients and the number of frames in each block and (b) the number of frames in each block.

Fig. 3
Fig. 3

(a) Sample raw image captured with the AMBER camera. The image in part (a) compensated for FPN using (b) two-point calibration and (c) the NC-based algorithm. (d) The RMSE at the k frame between the reference image and its corresponding corrected versions obtained using the NC-based algorithm, the CS algorithm, and the ASA algorithm.

Fig. 4
Fig. 4

NUC of real IR data captured with the FLIR camera. (a) A sample raw image and (b) the FPN compensated image obtained using the NC-based algorithm, with parameters K = 1300 and N = 10 .

Equations (7)

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Y i , j [ k ] = A i , j [ k ] X i , j [ k ] + B i , j [ k ] + V i , j [ k ] ,
Y i , j [ k ] = S i , j [ k ] + B i , j + V i , j [ k ] .
MSE = E { e [ k ] 2 } = R Y Y [ 0 ] 2 i = 0 N 1 h i R β Y [ i ] + i = 0 N 1 j = 0 N 1 h i h j R β β [ i j ] ,
[ h 0 h 1 h N 1 ] = [ R β β [ 0 ] R β β [ 1 ] R β β [ N 1 ] R β β [ 1 ] R β β [ 0 ] R β β [ N 2 ] R β β [ N 1 ] R β β [ N 2 ] R β β [ 0 ] ] 1 [ R β Y [ 0 ] R β Y [ 1 ] R β Y [ N 1 ] ] .
R β β [ n ] = β 0 2 ( 1 n K ) , R β Y [ n ] = β 0 ( 1 n K ) Y ¯ K n ,
S ^ [ k ] = Y [ k ] K Y ¯ K + [ K ( N 1 ) ] Y ¯ K N 2 K ( N 1 ) .
RMSE [ k ] = [ 1 P Q i = 0 P 1 j = 0 Q 1 ( S i , j [ k ] S ^ i , j [ k ] ) 2 ] 1 2 ,

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