Abstract

In uncooled long-wave infrared (LWIR) microbolometer imaging systems, temperature fluctuations of the focal plane array (FPA) result in thermal drift and spatial nonuniformity. In this paper, we present a novel approach based on single-image processing to simultaneously estimate temperature variances of FPAs and compensate the resulting temperature-dependent nonuniformity. Through well-controlled thermal calibrations, empirical behavioral models are derived to characterize the relationship between the responses of microbolometer and FPA temperature variations. Then, under the assumption that strong dependency exists between spatially adjacent pixels, we estimate the optimal FPA temperature so as to minimize the global intensity variance across the entire thermal infrared image. We make use of the estimated FPA temperature to infer an appropriate nonuniformity correction (NUC) profile. The performance and robustness of the proposed temperature-adaptive NUC method are evaluated on realistic IR images obtained by a 640×512 pixels uncooled LWIR microbolometer imaging system operating in a significantly changed temperature environment.

© 2013 Optical Society of America

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References

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  1. G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
    [CrossRef]
  2. J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
    [CrossRef]
  3. D. L. Perry and E. L. Dereniak, “Linear theory of nonuniformity correction in infrared staring sensors,” Opt. Eng. 32, 1854–1859 (1993).
    [CrossRef]
  4. J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
    [CrossRef]
  5. S. N. Torres, J. E. Pezoa, and M. M. Hayat, “Scene-based nonuniformity correction for focal plane arrays using the method of the inverse covariance form,” Appl. Opt. 42, 5872–5881 (2003).
    [CrossRef]
  6. 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]
  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. R. C. Hardie, M. M. Hayat, E. E. Armstrong, and B. Yasuda, “Scene-based nonuniformity correction using video sequences and registration,” Appl. Opt. 39, 1241–1250 (2000).
    [CrossRef]
  9. W. Qian, Q. Chen, G. Gu, and Z. Guan, “Correction method for stripe nonuniformity,” Appl. Opt. 49, 1764–1773 (2010).
    [CrossRef]
  10. Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
    [CrossRef]
  11. P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
    [CrossRef]

2013 (1)

P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
[CrossRef]

2012 (1)

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

2010 (3)

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

W. Qian, Q. Chen, G. Gu, and Z. Guan, “Correction method for stripe nonuniformity,” Appl. Opt. 49, 1764–1773 (2010).
[CrossRef]

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

2009 (1)

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

2003 (1)

2000 (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]

1993 (1)

D. L. Perry and E. L. Dereniak, “Linear theory of nonuniformity correction in infrared staring sensors,” Opt. Eng. 32, 1854–1859 (1993).
[CrossRef]

Armstrong, E.

Armstrong, E. E.

Battaglia, J.

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

Bieszczada, G.

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

Brubaker, R.

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

Cain, S. C.

Chen, Q.

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]

Delamere, M.

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

Dereniak, E. L.

D. L. Perry and E. L. Dereniak, “Linear theory of nonuniformity correction in infrared staring sensors,” Opt. Eng. 32, 1854–1859 (1993).
[CrossRef]

Franks, G.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Gilles, J.

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

Gu, G.

Guan, Z.

Hardie, R. C.

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]

Hayat, M. M.

Kasteka, M.

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

Landeau, S.

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

Laveigne, J.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Martin, C.

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

McHugh, S.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Morel, J.

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

Nazemi, J.

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

Nehring, B.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Nugent, P. W.

P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
[CrossRef]

Orzanowskia, T.

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

Perry, D. L.

D. L. Perry and E. L. Dereniak, “Linear theory of nonuniformity correction in infrared staring sensors,” Opt. Eng. 32, 1854–1859 (1993).
[CrossRef]

Pezoa, J. E.

Prewarski, M.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Pust, N. J.

P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
[CrossRef]

Qian, W.

Shaw, J. A.

P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
[CrossRef]

Sosnowskia, T.

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

Sparkman, K.

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Tendero, Y.

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

Torres, S. N.

Yasuda, B.

Appl. Opt. (4)

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]

Opt. Eng. (2)

P. W. Nugent, J. A. Shaw, and N. J. Pust, “Correcting for focal-plane-array temperature dependence in microbolometer infrared cameras lacking thermal stabilization,” Opt. Eng. 52, 061304 (2013).
[CrossRef]

D. L. Perry and E. L. Dereniak, “Linear theory of nonuniformity correction in infrared staring sensors,” Opt. Eng. 32, 1854–1859 (1993).
[CrossRef]

Proc. SPIE (4)

J. Nazemi, J. Battaglia, R. Brubaker, M. Delamere, and C. Martin, “A low-power, TEC-less, 1280 × 1024, compact SWIR camera with temperature-dependent, non-uniformity corrections,” Proc. SPIE 8353, 83530B (2012).
[CrossRef]

G. Bieszczada, T. Orzanowskia, T. Sosnowskia, and M. Kasteka, “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array,” Proc. SPIE 7481, 74810O (2009).
[CrossRef]

J. Laveigne, G. Franks, K. Sparkman, M. Prewarski, B. Nehring, and S. McHugh, “LWIR NUC using an uncooled microbolometer camera,” Proc. SPIE 7663, 766306 (2010).
[CrossRef]

Y. Tendero, J. Gilles, S. Landeau, and J. Morel, “Efficient single image non-uniformity correction algorithm,” Proc. SPIE 7834, 78340E (2010).
[CrossRef]

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Figures (9)

Fig. 1.
Fig. 1.

Image corrupted with FPN caused by temperature-dependent nonuniformity. (a) Raw data from an uncooled LWIR camera. We send serial comments to turn off its on-chip shutter-based NUC algorithm. Even very obvious objects are not recognizable before NUC. (b) NUC results based on an inaccurate FPA temperature measurement. Objects become recognizable, although temperature-sensitive spatial nonuniformity is still apparent. (c) Corrected output of our proposed method after performing simultaneous FPA temperature estimation and temperature-dependent NUC.

Fig. 2.
Fig. 2.

Flowchart of the proposed temperature-dependent NUC method.

Fig. 3.
Fig. 3.

Gain and offset parameters computed through two-point calibration when the FPA temperature was raised from 5°C to 65°C with 5°C interval. Every curve represents the estimated (a) gain and (b) offset parameters of a selected pixel at different FPA temperatures. Note the IR camera’s digital output is 14-bit.

Fig. 4.
Fig. 4.

Cumulative histogram of the gain standard variations. When FPA temperature changes from 5°C to 65°C, the standard variation of 15 gain values is less than 0.1 for 93.61% of the pixels.

Fig. 5.
Fig. 5.

Mean curve fitting errors of 640×512 calibrated offset parameters at different FPA temperatures using polynomial models of 1st degree, 2nd degree, and 3rd degree. More accurate curve fitting result can be achieved at the expense of increasing the complexity of the mathematical model. In our implementation, we choose the 2nd degree polynomial model for its simplicity and good fitting result.

Fig. 6.
Fig. 6.

We capture raw images of (a) a uniform blackbody and (b) a scene containing objects, shapes, and textures and test the proposed method for FPA temperature calculation.

Fig. 7.
Fig. 7.

Differences between the estimated T1 based on single-image processing and the temperature measurement TTS of temperature sensor at a number of temperature control points.

Fig. 8.
Fig. 8.

Standard deviation of a blackbody IR image using our proposed NUC algorithm and using NUC factors calibrated at 30°C. It is noted that our proposed method can adaptively compensate the temperature-related spatial nonuniformities (standard deviation remains below 10 digital counts).

Fig. 9.
Fig. 9.

RMSE between a reference frame (NUC result at 2.5°C) and the following corrected images (NUC result at 7.5°C, 17.5°C, 27.5°C, 37.5°C, 47.5°C, and 57.5°C).

Equations (8)

Equations on this page are rendered with MathJax. Learn more.

Zx,y=Ax,y(T1)×Sx,y+Bx,y(T1),
Bx,y(T1)=ax,y×T12+bx,y×T1+cx,y.
Δ=Δ1×T12+Δ2×T1+Δ3,
Δ2=Δ12·T14+2Δ1Δ2·T13+(2Δ1Δ3+Δ22)·T12+2Δ2Δ3·T1+Δ32.
Δ2=Δ12·T14+2Δ1Δ2·T13+(2Δ1Δ3+Δ22)·T12+2Δ2Δ3·T1+Δ32.
2Δ12·T13+3Δ1Δ2·T12+(2Δ1Δ3+Δ22)·T1+Δ2Δ3=0.
K=2Δ12,L=Δ1Δ2,M=2Δ1Δ3+Δ22,N=Δ2Δ3.
T1=LK+Q+Q2+R33+QQ2+R33,

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