Abstract

The emergence of IR hyperspectral sensors in recent years enables their use in remote environmental monitoring of gaseous plumes. IR hyperspectral imaging combines the unique advantages of traditional remote sensing methods such as multispectral imagery and nonimaging Fourier transform infrared spectroscopy, while eliminating their drawbacks. The most significant improvement introduced by hyperspectral technology is the capability of standoff detection and discrimination of effluent gaseous plumes without need for a clear reference background or any other temporal information. We introduce a novel approach for detection and discrimination of gaseous plumes in IR hyperspectral imagery using a divisive hierarchical clustering algorithm. The utility of the suggested detection algorithm is demonstrated on IR hyperspectral images of the release of two atmospheric tracers. The application of the proposed detection method on the experimental data has yielded a correct identification of all the releases without any false alarms. These encouraging results show that the presented approach can be used as a basis for a complete identification algorithm for gaseous pollutants in IR hyperspectral imagery without the need for a clear background.

© 2007 Optical Society of America

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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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2006

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

E. Agassi and E. Hirsch, "Remote detection of SF6 plumes in a stable boundary layer," Proc. SPIE 5988, 131-141 (2006).

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

T. Burr and B. R. Foy, "Characterizing clutter in the context of detecting weak gaseous plumes in hyperspectral imagery," Sensors 6, 1587-1615 (2006).

T. Burr and N. Hegarther, "Overview of physical models and statistical approaches for weak gaseous plume detection using passive infrared hyperspectral imagery," Sensors 6, 1721-1750 (2006).

J. Theiler, B. R. Foy, and A. M. Fraser, "Nonlinear signal contamination effects for gaseous plume detection in hyperspectral imagery," Proc. SPIE 6233, 62331U (2006).
[CrossRef]

J. Theiler and B. R. Foy, "The effect of signal contamination in matched-filter detection of the signal on a cluttered background," IEEE Geosci. Remote Sens. Lett. 3, 98-102 (2006).
[CrossRef]

2005

J. Theiler, B. R. Foy, and A. M. Fraser, "Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery," Proc. SPIE 5806, 182-193 (2005).
[CrossRef]

2004

D. W. Messinger, "Gaseous plume detection in hyperspectral images: a comparison of methods," Proc. SPIE 5425, 592-603 (2004).
[CrossRef]

J. Sandsten, H. Edner, and S. Svanberg, "Gas visualization of industrial hydrocarbon emissions," Opt. Express 12, 1443-1451 (2004).
[CrossRef]

2003

Y. Guern, L. Grenier, and F. Carpentier, "Uncooled IRFPA for low-cost multispectral/hyperspectral LWIR imaging device," Proc. SPIE 5093, 126-135 (2003).
[CrossRef]

M. Hinnrichs and B. Piatek, "Hand held hyperspectral imager for chemical/biological and environmental applications," Proc. SPIE 5270, 10-18 (2003).
[CrossRef]

2002

S. J. Young, "Detection and quantification of gases in industrial-stack plumes using thermal-infrared hyperspectral imaging," Tech. Rep. ATR-2002(8407)-1 (The Aerospace Corporation, 2002).

2001

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. (Wiley, 2001).

2000

1998

L. Grenier, G. Pelous, and P. Adam, "Passive stand-off detection of gas clouds in open field by IR imagery," Proc. SPIE 3553, 86-92 (1998).

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

A. Iffarraguerri and C. Gittins, "Chemical cloud mapping and identification using convex cone analysis of AIRIS multispectral imaging data," Proc. SPIE 3533, 114-121 (1998).
[CrossRef]

1997

B. Jahne, Digital Image Processing (Springer-Verlag, 1997).

1996

1995

1994

J. C. Harsanyi and C.-I. Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geosci. Remote Sens. 32, 794-795 (1994).

R. T. Behrens and L. L. Scharf, "Signal processing applications of oblique projection operators," IEEE Trans. Signal Process. 42, 1413-1424 (1994).
[CrossRef]

1988

Adam, P.

L. Grenier, G. Pelous, and P. Adam, "Passive stand-off detection of gas clouds in open field by IR imagery," Proc. SPIE 3553, 86-92 (1998).

Agassi, E.

E. Agassi and E. Hirsch, "Remote detection of SF6 plumes in a stable boundary layer," Proc. SPIE 5988, 131-141 (2006).

Behrens, R. T.

R. T. Behrens and L. L. Scharf, "Signal processing applications of oblique projection operators," IEEE Trans. Signal Process. 42, 1413-1424 (1994).
[CrossRef]

Beil, A.

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

Boerl, C. C.

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

Boyce, B.

Burr, T.

T. Burr and B. R. Foy, "Characterizing clutter in the context of detecting weak gaseous plumes in hyperspectral imagery," Sensors 6, 1587-1615 (2006).

T. Burr and N. Hegarther, "Overview of physical models and statistical approaches for weak gaseous plume detection using passive infrared hyperspectral imagery," Sensors 6, 1721-1750 (2006).

Carlson, R. C.

Carpentier, F.

Y. Guern, L. Grenier, and F. Carpentier, "Uncooled IRFPA for low-cost multispectral/hyperspectral LWIR imaging device," Proc. SPIE 5093, 126-135 (2003).
[CrossRef]

Chamberland, M.

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

Chang, C.-I.

J. C. Harsanyi and C.-I. Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geosci. Remote Sens. 32, 794-795 (1994).

Daum, R.

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

Duda, R.

R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. (Wiley, 2001).

Edner, H.

Farley, V.

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

Flanigan, D. F.

Foy, B. R.

J. Theiler and B. R. Foy, "The effect of signal contamination in matched-filter detection of the signal on a cluttered background," IEEE Geosci. Remote Sens. Lett. 3, 98-102 (2006).
[CrossRef]

T. Burr and B. R. Foy, "Characterizing clutter in the context of detecting weak gaseous plumes in hyperspectral imagery," Sensors 6, 1587-1615 (2006).

J. Theiler, B. R. Foy, and A. M. Fraser, "Nonlinear signal contamination effects for gaseous plume detection in hyperspectral imagery," Proc. SPIE 6233, 62331U (2006).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery," Proc. SPIE 5806, 182-193 (2005).
[CrossRef]

Fraser, A. M.

J. Theiler, B. R. Foy, and A. M. Fraser, "Nonlinear signal contamination effects for gaseous plume detection in hyperspectral imagery," Proc. SPIE 6233, 62331U (2006).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery," Proc. SPIE 5806, 182-193 (2005).
[CrossRef]

Funk, C. T.

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

Gelb, A. H.

Gerhard, H. H.

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

Gerhard, J. H.

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

Gittins, C.

A. Iffarraguerri and C. Gittins, "Chemical cloud mapping and identification using convex cone analysis of AIRIS multispectral imaging data," Proc. SPIE 3533, 114-121 (1998).
[CrossRef]

Gittins, C. M.

Green, B. D.

Grenier, L.

Y. Guern, L. Grenier, and F. Carpentier, "Uncooled IRFPA for low-cost multispectral/hyperspectral LWIR imaging device," Proc. SPIE 5093, 126-135 (2003).
[CrossRef]

L. Grenier, G. Pelous, and P. Adam, "Passive stand-off detection of gas clouds in open field by IR imagery," Proc. SPIE 3553, 86-92 (1998).

Guern, Y.

Y. Guern, L. Grenier, and F. Carpentier, "Uncooled IRFPA for low-cost multispectral/hyperspectral LWIR imaging device," Proc. SPIE 5093, 126-135 (2003).
[CrossRef]

Hall, J. L.

Harig, R.

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

Harsanyi, J. C.

J. C. Harsanyi and C.-I. Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geosci. Remote Sens. 32, 794-795 (1994).

Hart, P.

R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. (Wiley, 2001).

Hayden, A.

Hayden, A. F.

Hegarther, N.

T. Burr and N. Hegarther, "Overview of physical models and statistical approaches for weak gaseous plume detection using passive infrared hyperspectral imagery," Sensors 6, 1721-1750 (2006).

Herr, K. C.

Hinnrichs, M.

M. Hinnrichs and B. Piatek, "Hand held hyperspectral imager for chemical/biological and environmental applications," Proc. SPIE 5270, 10-18 (2003).
[CrossRef]

Hirsch, E.

E. Agassi and E. Hirsch, "Remote detection of SF6 plumes in a stable boundary layer," Proc. SPIE 5988, 131-141 (2006).

Iffarraguerri, A.

A. Iffarraguerri and C. Gittins, "Chemical cloud mapping and identification using convex cone analysis of AIRIS multispectral imaging data," Proc. SPIE 3533, 114-121 (1998).
[CrossRef]

Jahne, B.

B. Jahne, Digital Image Processing (Springer-Verlag, 1997).

Legault, J.

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

Marinelli, W. J.

Matz, G.

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

McGonigle, J. S.

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

Messinger, D. W.

D. W. Messinger, "Gaseous plume detection in hyperspectral images: a comparison of methods," Proc. SPIE 5425, 592-603 (2004).
[CrossRef]

Niple, E.

Oppenheimer, C.

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

Pelous, G.

L. Grenier, G. Pelous, and P. Adam, "Passive stand-off detection of gas clouds in open field by IR imagery," Proc. SPIE 3553, 86-92 (1998).

Piatek, B.

M. Hinnrichs and B. Piatek, "Hand held hyperspectral imager for chemical/biological and environmental applications," Proc. SPIE 5270, 10-18 (2003).
[CrossRef]

Polak, M. L.

Roberts, D. A.

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

Rusch, P.

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

Sandsten, J.

Scharf, L. L.

R. T. Behrens and L. L. Scharf, "Signal processing applications of oblique projection operators," IEEE Trans. Signal Process. 42, 1413-1424 (1994).
[CrossRef]

Stork, D.

R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. (Wiley, 2001).

Svanberg, S.

Telfair, W. B.

Theiler, J.

J. Theiler and B. R. Foy, "The effect of signal contamination in matched-filter detection of the signal on a cluttered background," IEEE Geosci. Remote Sens. Lett. 3, 98-102 (2006).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Nonlinear signal contamination effects for gaseous plume detection in hyperspectral imagery," Proc. SPIE 6233, 62331U (2006).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery," Proc. SPIE 5806, 182-193 (2005).
[CrossRef]

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

Thomson, C. L.

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

Tsanev, V. I.

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

Vallières, A.

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

Young, S. J.

S. J. Young, "Detection and quantification of gases in industrial-stack plumes using thermal-infrared hyperspectral imaging," Tech. Rep. ATR-2002(8407)-1 (The Aerospace Corporation, 2002).

Appl. Opt.

Atmos. Environ.

J. S. McGonigle, C. L. Thomson, V. I. Tsanev, and C. Oppenheimer, "A simple technique for measuring power station SO2 and NO2 emissions," Atmos. Environ. 38, 21-25 (2001).
[CrossRef]

IEEE Geosci. Remote Sens. Lett.

J. Theiler and B. R. Foy, "The effect of signal contamination in matched-filter detection of the signal on a cluttered background," IEEE Geosci. Remote Sens. Lett. 3, 98-102 (2006).
[CrossRef]

IEEE Trans. Geosci. Remote Sens.

C. T. Funk, J. Theiler, D. A. Roberts, and C. C. Boerl, "Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery," IEEE Trans. Geosci. Remote Sens. 39, 1410-1420 (2001).
[CrossRef]

J. C. Harsanyi and C.-I. Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geosci. Remote Sens. 32, 794-795 (1994).

IEEE Trans. Signal Process.

R. T. Behrens and L. L. Scharf, "Signal processing applications of oblique projection operators," IEEE Trans. Signal Process. 42, 1413-1424 (1994).
[CrossRef]

Opt. Express

Proc. SPIE

R. Harig, G. Matz, P., Rusch, H. H. Gerhard, and J. H. Gerhard, "New scanning infrared gas imaging system (SIGIS 2) for emergency response," Proc. SPIE 5995, 174-181 (2006).

E. Agassi and E. Hirsch, "Remote detection of SF6 plumes in a stable boundary layer," Proc. SPIE 5988, 131-141 (2006).

L. Grenier, G. Pelous, and P. Adam, "Passive stand-off detection of gas clouds in open field by IR imagery," Proc. SPIE 3553, 86-92 (1998).

Y. Guern, L. Grenier, and F. Carpentier, "Uncooled IRFPA for low-cost multispectral/hyperspectral LWIR imaging device," Proc. SPIE 5093, 126-135 (2003).
[CrossRef]

M. Hinnrichs and B. Piatek, "Hand held hyperspectral imager for chemical/biological and environmental applications," Proc. SPIE 5270, 10-18 (2003).
[CrossRef]

V. Farley, A. Vallières, M. Chamberland, and J. Legault, "Performance of the FIRST, a longwave infrared hyperspectral imaging sensor," Proc. SPIE 6398 (2006).

A. Iffarraguerri and C. Gittins, "Chemical cloud mapping and identification using convex cone analysis of AIRIS multispectral imaging data," Proc. SPIE 3533, 114-121 (1998).
[CrossRef]

A. Beil, R. Daum, R. Harig, and G. Matz, "Remote sensing of atmospheric pollution by passive FTIR spectroscopy," Proc. SPIE 3493, 32-43 (1998).
[CrossRef]

D. W. Messinger, "Gaseous plume detection in hyperspectral images: a comparison of methods," Proc. SPIE 5425, 592-603 (2004).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Nonlinear signal contamination effects for gaseous plume detection in hyperspectral imagery," Proc. SPIE 6233, 62331U (2006).
[CrossRef]

J. Theiler, B. R. Foy, and A. M. Fraser, "Characterizing non-Gaussian clutter and detecting weak gaseous plumes in hyperspectral imagery," Proc. SPIE 5806, 182-193 (2005).
[CrossRef]

Sensors

T. Burr and B. R. Foy, "Characterizing clutter in the context of detecting weak gaseous plumes in hyperspectral imagery," Sensors 6, 1587-1615 (2006).

T. Burr and N. Hegarther, "Overview of physical models and statistical approaches for weak gaseous plume detection using passive infrared hyperspectral imagery," Sensors 6, 1721-1750 (2006).

Other

S. J. Young, "Detection and quantification of gases in industrial-stack plumes using thermal-infrared hyperspectral imaging," Tech. Rep. ATR-2002(8407)-1 (The Aerospace Corporation, 2002).

R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. (Wiley, 2001).

B. Jahne, Digital Image Processing (Springer-Verlag, 1997).

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Figures (10)

Fig. 1
Fig. 1

(Color online) Different background spectra with an SF 6 plume. The SF 6 transmittance spectrum is plotted in black.

Fig. 2
Fig. 2

Backgrounds of the different scenes.

Fig. 3
Fig. 3

Our divisive hierarchical algorithm scheme.

Fig. 4
Fig. 4

Example of the initial spectral-spatial decomposition step: (a) The binary results of the first spectral K-means (K = 2). One cluster is colored black and the other is colored white. (b) The result of the spatial segmentation algorithm on the first spectral cluster [black in (a)]. (c) The result of the spatial segmentation algorithm on the second spectral cluster [white in (a)].

Fig. 5
Fig. 5

(Color online) Image segmentation after successive numbers of iterations of the divisive hierarchical spatial-spectral decomposition algorithm.

Fig. 6
Fig. 6

(Color online) Final result of the spatial-spectral decomposition algorithm on one of the scenes.

Fig. 7
Fig. 7

(Color online) Spectral cross-correlation matrix of the various segments. High correlation values indicate spectrally similar segments, but our algorithm ensures they are spatially separated.

Fig. 8
Fig. 8

Illustration of the detection algorithm assumption.

Fig. 9
Fig. 9

Second stage of the algorithm scheme.

Fig. 10
Fig. 10

(Color online) Result of the identification stage of the detection algorithm for CHF 3 and SF 6 plumes, released simultaneously.

Tables (1)

Tables Icon

Table 1 Technical Parameters of the FIRST Hyperspectral Sensor

Equations (6)

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

W ( λ ) = B ( λ , T b g d ) exp [ α ( λ ) 0 R C ( r ) d r ] + B ( λ , T c l d ) { 1 exp [ α ( λ ) 0 R C ( r ) d r ] } ,
B ( λ , T s ) B ( λ , T c l d ) = τ ( λ ) [ B ( λ , T b g d ) B ( λ , T c l d ) ] .
( T s T c l d ) B T | T s τ ( λ ) ( T b g d T c l d ) B T | T b g d .
τ ( λ ) = T s T c l d T b g d T c l d .
d i s t ( T 1 , T 2 ) = 1 c o r r ( T 1 , T 2 ) = 1 E [ ( T 1 μ 1 ) ( T 2 μ 2 ) ] E [ ( T 1 μ 1 ) 2 ] E [ ( T 2 μ 2 ) 2 ] ,
E [ ( T i μ i ) ( T j μ j ) ] E [ ( T i μ i ) 2 ] E [ ( T j μ j ) 2 ] ,

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