Abstract

Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, which is a typical example of a push-broom instrument exhibiting a relatively high noise component. The proposed correction method is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. A technique to exclude the contribution of the spatial high frequencies of the surface from the destriping process is introduced. First, the performance of the proposed algorithm is tested on a set of realistic synthetic images with added modeled noise in order to quantify the noise reduction and the noise estimation accuracy. Then, algorithm robustness is tested on more than 350 real CHRIS images from different sites, several acquisition modes (different spatial and spectral resolutions), and covering the full range of possible sensor temperatures. The proposed algorithm is benchmarked against the CHRIS reference algorithm. Results show excellent rejection of the noise pattern with respect to the original CHRIS images, especially improving the removal in those scenes with a natural high contrast. However, some low-frequency components still remain. In addition, the developed correction model captures and corrects the dependency of the noise patterns on sensor temperature, which confirms the robustness of the presented approach.

© 2008 Optical Society of America

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    [CrossRef]
  2. M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
    [CrossRef]
  3. A. Barducci and I. Pippi, “Analysis and rejection of systematic disturbances in hyperspectral remotely sensed images of the Earth,” Appl. Opt. 40, 1464-1477 (2001).
    [CrossRef]
  4. A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.
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    [CrossRef]
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    [CrossRef] [PubMed]
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    [CrossRef]
  8. D. Bernaerts, F. Teston, and J. Bermyn, “PROBA (Project for Onboard Autonomy),” presented at the 5th International Symposium on Systems and Services for Small Satellites (La Baule, France, 2000).
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  10. L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
    [CrossRef]
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  13. S. N. Torres, J. E. Pezoa, and M. M. Hayat, “Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form,” Appl. Opt. 42, 5872-5881(2003).
    [CrossRef] [PubMed]
  14. J. E. Pezoa, M. M. Hayat, S. N. Torres, and M. S. Rahman, “Multimodel Kalman filtering for adaptive nonuniformity correction in infrared sensors,” J. Opt. Soc. Am. A 23, 1282-1291(2006).
    [CrossRef]
  15. F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
    [CrossRef]
  16. J. Garcia and J. Moreno, “Removal of noises in CHRIS/Proba images: Application to the SPARC campaign data,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 9_GARCIA.pdf.
  17. J. Settle and M. Cutter, “HDFclean V2. A program for reprocessing images captured by the CHRIS hyper-spectral imager” (2005), http://earth.esa.int/proba/.
  18. P. Mlsna and T. Becker, “Striping artifact reduction in lunar orbiter mosaic images,” in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation (IEEE Computer Society, 2006), pp. 95-99.
    [CrossRef]
  19. R. Leathers, T. Downes, and R. Priest, “Scene-based nonuniformity corrections for optical and SWIR pushbroom sensors,” Opt. Express 13, 5136-5150 (2005).
    [CrossRef] [PubMed]
  20. L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
    [CrossRef]
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  22. The BEAM Toolbox is a collection of open-source executable tools supported by ESA to facilitate the utilization, viewing, and processing of ESA Earth observation data. More information is available at http://envisat.esa.int/resources/softwaretools/ or http://www.brockmann-consult.de/beam/.
  23. CHRIS products are provided in top of the atmosphere radiance in a HDF v4 file format, which includes additional acquisition information (image date, azimuth and zenith view angles, etc.) contained in the metadata attributes of the CHRIS HDF file .
  24. L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
    [CrossRef]
  25. M. Cutter and L. Johns, “CHRIS data format,” SIRA Tech. Rep. Issue 4.2 (European Space Agency, 2005), document 271.DO.13, http://earth.esa.int/proba/.
  26. R. Larsen, A. A. Nielsen, and K. Conradsen, “Restoration of hyperspectral push-broom scanner data,” in Proceedings of the 17th EARSeL Symposium on Future Trends in Remote Sensing,” P. Gudmandsen, ed. (A. A. Balkema, 1998), pp. 157-162.
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    [CrossRef]
  29. H. Othman and S.-E. Qian, “Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage,” IEEE Trans. Geosci. Remote Sensing 44, 397-408 (2006).
    [CrossRef]
  30. L. L. Lapin, Probability and Statistics for Modern Engineering (Duxbury, PWS Publishers, 1983).

2006 (4)

L. Guanter, R. Richter, and J. Moreno, “Spectral calibration of hyperspectral imagery using atmospheric absorption features,” Appl. Opt. 45, 2360-2370 (2006).
[CrossRef] [PubMed]

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

J. E. Pezoa, M. M. Hayat, S. N. Torres, and M. S. Rahman, “Multimodel Kalman filtering for adaptive nonuniformity correction in infrared sensors,” J. Opt. Soc. Am. A 23, 1282-1291(2006).
[CrossRef]

H. Othman and S.-E. Qian, “Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage,” IEEE Trans. Geosci. Remote Sensing 44, 397-408 (2006).
[CrossRef]

2005 (3)

R. Leathers, T. Downes, and R. Priest, “Scene-based nonuniformity corrections for optical and SWIR pushbroom sensors,” Opt. Express 13, 5136-5150 (2005).
[CrossRef] [PubMed]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
[CrossRef]

2004 (3)

N. Keshava, “Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries,” IEEE Trans. Geosci. Remote Sensing 42, 1552-1565 (2004).
[CrossRef]

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
[CrossRef]

2003 (1)

2002 (1)

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

2001 (1)

2000 (2)

P. Mouroulis, R. O. Green, and T. G. Chrien, “Design of pushbroom imaging spectrometers for optimum recovery of spectroscopic and spatial information,” Appl. Opt. 39, 2210-2220 (2000).
[CrossRef]

F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
[CrossRef]

Aiazzi, B.

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

Alonso, L.

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
[CrossRef]

Alparone, L.

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

Amorós, J.

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Barducci, A.

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

A. Barducci and I. Pippi, “Analysis and rejection of systematic disturbances in hyperspectral remotely sensed images of the Earth,” Appl. Opt. 40, 1464-1477 (2001).
[CrossRef]

A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.

Barnsley, M.

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

Baronti, S.

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

Becker, T.

P. Mlsna and T. Becker, “Striping artifact reduction in lunar orbiter mosaic images,” in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation (IEEE Computer Society, 2006), pp. 95-99.
[CrossRef]

Bermyn, J.

D. Bernaerts, F. Teston, and J. Bermyn, “PROBA (Project for Onboard Autonomy),” presented at the 5th International Symposium on Systems and Services for Small Satellites (La Baule, France, 2000).

Bernaerts, D.

D. Bernaerts, F. Teston, and J. Bermyn, “PROBA (Project for Onboard Autonomy),” presented at the 5th International Symposium on Systems and Services for Small Satellites (La Baule, France, 2000).

Brando, V. E.

M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
[CrossRef]

Brockmann, C.

N. Fomferra and C. Brockmann, “BEAM--the ENVISAT MERIS and AATSR Toolbox,” in “ Proceedings of the MERIS (A) ATSR Workshop 2005,” ESA SP-597 (European Space Agency, 2005), paper paper_Fomferra.pdf.

Calpe, J.

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Camps-Valls, G.

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Chrien, T. G.

Conradsen, K.

R. Larsen, A. A. Nielsen, and K. Conradsen, “Restoration of hyperspectral push-broom scanner data,” in Proceedings of the 17th EARSeL Symposium on Future Trends in Remote Sensing,” P. Gudmandsen, ed. (A. A. Balkema, 1998), pp. 157-162.

Csillag, F.

F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
[CrossRef]

Cutter, M.

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

M. Cutter and L. Johns, “CHRIS data products--latest issue,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 05_cutter.pdf.

M. Cutter, “Review of aspects associated with the CHRIS calibration,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 6_cutter.pdf.

J. Settle and M. Cutter, “HDFclean V2. A program for reprocessing images captured by the CHRIS hyper-spectral imager” (2005), http://earth.esa.int/proba/.

M. Cutter and L. Johns, “CHRIS data format,” SIRA Tech. Rep. Issue 4.2 (European Space Agency, 2005), document 271.DO.13, http://earth.esa.int/proba/.

Dekker, A. G.

M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
[CrossRef]

Downes, T.

Fomferra, N.

N. Fomferra and C. Brockmann, “BEAM--the ENVISAT MERIS and AATSR Toolbox,” in “ Proceedings of the MERIS (A) ATSR Workshop 2005,” ESA SP-597 (European Space Agency, 2005), paper paper_Fomferra.pdf.

Fortea, J.

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Gadallah, F.

F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
[CrossRef]

Garcia, J.

J. Garcia and J. Moreno, “Removal of noises in CHRIS/Proba images: Application to the SPARC campaign data,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 9_GARCIA.pdf.

Gómez-Chova, L.

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Green, R. O.

Guanter, L.

L. Guanter, R. Richter, and J. Moreno, “Spectral calibration of hyperspectral imagery using atmospheric absorption features,” Appl. Opt. 45, 2360-2370 (2006).
[CrossRef] [PubMed]

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
[CrossRef]

Guzzi, D.

A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.

Hayat, M. M.

Johns, L.

M. Cutter and L. Johns, “CHRIS data format,” SIRA Tech. Rep. Issue 4.2 (European Space Agency, 2005), document 271.DO.13, http://earth.esa.int/proba/.

M. Cutter and L. Johns, “CHRIS data products--latest issue,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 05_cutter.pdf.

Keshava, N.

N. Keshava, “Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries,” IEEE Trans. Geosci. Remote Sensing 42, 1552-1565 (2004).
[CrossRef]

Lapin, L. L.

L. L. Lapin, Probability and Statistics for Modern Engineering (Duxbury, PWS Publishers, 1983).

Larsen, R.

R. Larsen, A. A. Nielsen, and K. Conradsen, “Restoration of hyperspectral push-broom scanner data,” in Proceedings of the 17th EARSeL Symposium on Future Trends in Remote Sensing,” P. Gudmandsen, ed. (A. A. Balkema, 1998), pp. 157-162.

Leathers, R.

Lobb, D.

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

Marcoionni, P.

A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.

Martín, J.

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

Mlsna, P.

P. Mlsna and T. Becker, “Striping artifact reduction in lunar orbiter mosaic images,” in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation (IEEE Computer Society, 2006), pp. 95-99.
[CrossRef]

Moreno, J.

L. Guanter, R. Richter, and J. Moreno, “Spectral calibration of hyperspectral imagery using atmospheric absorption features,” Appl. Opt. 45, 2360-2370 (2006).
[CrossRef] [PubMed]

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
[CrossRef]

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
[CrossRef]

J. Garcia and J. Moreno, “Removal of noises in CHRIS/Proba images: Application to the SPARC campaign data,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 9_GARCIA.pdf.

Mouroulis, P.

Nielsen, A. A.

R. Larsen, A. A. Nielsen, and K. Conradsen, “Restoration of hyperspectral push-broom scanner data,” in Proceedings of the 17th EARSeL Symposium on Future Trends in Remote Sensing,” P. Gudmandsen, ed. (A. A. Balkema, 1998), pp. 157-162.

Othman, H.

H. Othman and S.-E. Qian, “Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage,” IEEE Trans. Geosci. Remote Sensing 44, 397-408 (2006).
[CrossRef]

Pezoa, J. E.

Pippi, I.

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
[CrossRef]

A. Barducci and I. Pippi, “Analysis and rejection of systematic disturbances in hyperspectral remotely sensed images of the Earth,” Appl. Opt. 40, 1464-1477 (2001).
[CrossRef]

A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.

Pratt, W. K.

W. K. Pratt, Digital Image Processing: PIKS Inside, 3rd ed. (Wiley, 2001).

Priest, R.

Qian, S.-E.

H. Othman and S.-E. Qian, “Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage,” IEEE Trans. Geosci. Remote Sensing 44, 397-408 (2006).
[CrossRef]

Rahman, M. S.

Richter, R.

Settle, J.

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

J. Settle and M. Cutter, “HDFclean V2. A program for reprocessing images captured by the CHRIS hyper-spectral imager” (2005), http://earth.esa.int/proba/.

Smith, E.

F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
[CrossRef]

Teston, F.

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

D. Bernaerts, F. Teston, and J. Bermyn, “PROBA (Project for Onboard Autonomy),” presented at the 5th International Symposium on Systems and Services for Small Satellites (La Baule, France, 2000).

Theuwissen, A.

A. Theuwissen, Solid-State Imaging with Charge-Coupled Devices (Kluwer Academic, 1995).

Torres, S. N.

Wettle, M.

M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
[CrossRef]

Appl. Opt. (4)

IEEE Trans. Geosci. Remote Sensing (4)

M. Barnsley, J. Settle, M. Cutter, D. Lobb, and F. Teston, “The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere,” IEEE Trans. Geosci. Remote Sensing 42, 1512-1520(2004).
[CrossRef]

L. Guanter, L. Alonso, and J. Moreno, “A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns,” IEEE Trans. Geosci. Remote Sensing 43, 2908-2917 (2005).
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N. Keshava, “Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries,” IEEE Trans. Geosci. Remote Sensing 42, 1552-1565 (2004).
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H. Othman and S.-E. Qian, “Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage,” IEEE Trans. Geosci. Remote Sensing 44, 397-408 (2006).
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Int. J. Remote Sensing (1)

F. Gadallah, F. Csillag, and E. Smith, “Destriping multisensor imagery with moment matching,” Int. J. Remote Sensing 21, 2505-2511 (2000).
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J. Opt. Soc. Am. A (1)

Opt. Eng. (1)

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, “Estimating noise and information for multispectral imagery,” Opt. Eng. 41, 656-668 (2002).
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Opt. Express (1)

Proc. SPIE (2)

L. Gómez-Chova, J. Amorós, G. Camps-Valls, J. Martín, J. Calpe, L. Alonso, L. Guanter, J. Fortea, and J. Moreno, “Cloud detection for CHRIS/Proba hyperspectral images,” Proc. SPIE 5979, 59791Q (2005)
[CrossRef]

L. Gómez-Chova, L. Alonso, L. Guanter, G. Camps-Valls, J. Calpe, and J. Moreno, “Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data,” Proc. SPIE 6365, 63650Z (2006).
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Remote Sens. Environ. (1)

M. Wettle, V. E. Brando, and A. G. Dekker, “A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef,” Remote Sens. Environ. 93, 188-197 (2004).
[CrossRef]

Other (15)

A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, “CHRIS-PROBA performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 09_bardu.pdf.

D. Bernaerts, F. Teston, and J. Bermyn, “PROBA (Project for Onboard Autonomy),” presented at the 5th International Symposium on Systems and Services for Small Satellites (La Baule, France, 2000).

M. Cutter and L. Johns, “CHRIS data products--latest issue,” in “Proceedings of Third CHRIS/Proba Workshop,,” ESA-SP-593 (European Space Agency, 2005), paper 05_cutter.pdf.

A. Theuwissen, Solid-State Imaging with Charge-Coupled Devices (Kluwer Academic, 1995).

M. Cutter, “Review of aspects associated with the CHRIS calibration,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 6_cutter.pdf.

J. Garcia and J. Moreno, “Removal of noises in CHRIS/Proba images: Application to the SPARC campaign data,” in “Proceedings of the 2nd CHRIS/Proba Workshop,” ESA SP-578 (European Space Agency, 2004), paper 9_GARCIA.pdf.

J. Settle and M. Cutter, “HDFclean V2. A program for reprocessing images captured by the CHRIS hyper-spectral imager” (2005), http://earth.esa.int/proba/.

P. Mlsna and T. Becker, “Striping artifact reduction in lunar orbiter mosaic images,” in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation (IEEE Computer Society, 2006), pp. 95-99.
[CrossRef]

N. Fomferra and C. Brockmann, “BEAM--the ENVISAT MERIS and AATSR Toolbox,” in “ Proceedings of the MERIS (A) ATSR Workshop 2005,” ESA SP-597 (European Space Agency, 2005), paper paper_Fomferra.pdf.

The BEAM Toolbox is a collection of open-source executable tools supported by ESA to facilitate the utilization, viewing, and processing of ESA Earth observation data. More information is available at http://envisat.esa.int/resources/softwaretools/ or http://www.brockmann-consult.de/beam/.

CHRIS products are provided in top of the atmosphere radiance in a HDF v4 file format, which includes additional acquisition information (image date, azimuth and zenith view angles, etc.) contained in the metadata attributes of the CHRIS HDF file .

M. Cutter and L. Johns, “CHRIS data format,” SIRA Tech. Rep. Issue 4.2 (European Space Agency, 2005), document 271.DO.13, http://earth.esa.int/proba/.

R. Larsen, A. A. Nielsen, and K. Conradsen, “Restoration of hyperspectral push-broom scanner data,” in Proceedings of the 17th EARSeL Symposium on Future Trends in Remote Sensing,” P. Gudmandsen, ed. (A. A. Balkema, 1998), pp. 157-162.

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Figures (11)

Fig. 1
Fig. 1

Design of a push-broom imaging spectrometer that shows its operation mode and the sources of the coherent spatial noise patterns: entrance slit width that depends on temperature (T), and CCD sensitivity (figure based on [3]).

Fig. 2
Fig. 2

Formation process of the VS, ν ( p , b ) , from the combination of the nonuniform CCD pixel response, S ( p , b ) , and the slit optical response, H x ( p ) , which are constant in columns.

Fig. 3
Fig. 3

Example of the processing steps of two different VS reduction methods proposed in (a) [3] and (b) [17] (profiles of the last band of CHRIS_EI_060130_63A1_41 image taken over Heron Island).

Fig. 4
Fig. 4

Example of the processing steps of proposed VS correction method (profiles of the last band of CHRIS_EI_060130_63A1_41 image taken over Heron Island).

Fig. 5
Fig. 5

Pictures of the CHRIS original (upper row) and synthetic noise-free (lower row) images over the test sites of BR-2005-07-17 (mode 1), EI-2006-01-30 (mode 2), and PC-2005-05-18 (mode 2).

Fig. 6
Fig. 6

Synthetic multiplicative noise (first 250 image columns shown for proper visualization). (a) Noise profile coming from the entrance slit (slit VS). (b) Noise profile applied to each spectral band that is obtained multiplying the slit VS by the CCD response for each band in the across-track direction.

Fig. 7
Fig. 7

Performance of the proposed method in the estimation of the VS of image BR-2005-07-17 (mode 1): (a) actual and estimated VS; (b) actual versus estimated correction factors.

Fig. 8
Fig. 8

Scatterplot of the standard deviation of the estimated VS factors (computed for each acquisition within the five angles) for both methods.

Fig. 9
Fig. 9

Example of the noise reduction results on real CHRIS images over the test sites of Lanier (Canada, LR-2005-02-22, mode 1), Reynold’s Creek (USA, RC-2004-04-23, mode 1), and Rame Head (UK, RH-2003-03-06, mode 2): original CHRIS product (left column), the image corrected with the algorithm implemented in [17] (center column), and the image processed with the proposed algorithm (right column).

Fig. 10
Fig. 10

Dependence of CHRIS slit VS on temperature. From left to right: (a) detail of the slit-VS profiles for all the mode 2 acquisitions of the database ( H ( p , T ) and H ( x , T ) ); (b) across-track shift of the slit-VS shape as a function of temperature ( Δ x ( T ) ); (c) scaling of the slit VS factors as a function of temperature ( G H ( T ) ).

Fig. 11
Fig. 11

(a) Detail of the real slit VS H modeled from mode 1 and mode 2 CHRIS images, and the binning of mode 2 closely matching the mode 1 curve. (b) Scatterplot of the modeled mode 1 and mode 2 real slit VS.

Tables (1)

Tables Icon

Table 1 Mean error (ME), mean absolute error (MAE), and root mean-squared error (RMSE) for actual and estimated VS correction factors for synthetic images

Equations (15)

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I ( l , p , b ) = S ( p , b ) y l x p λ b L ( y , x , λ ) H ( x , λ ) d y d x d λ + S 0 ( l , p , b ) ,
y l x p λ b L ( y , x , λ ) H ( x ) H ( λ ) d y d x d λ = L ( l , p , b ) H x ( p ) H λ ( b ) ,
I ( l , p , b ) = L ( l , p , b ) H x ( p ) H λ ( b ) S ( p , b ) + S 0 ( l , p , b ) .
I ( l , p , b ) = L ( l , p , b ) H ( p ) S ( p , b ) = L ( l , p , b ) ν ( p , b ) ,
D all ( l , b ) = [ I ( l , p , b ) I ( l , p + 1 , b ) ] 2 , p = 1 , 2 , , N p 1 ,
D even ( l , b ) = [ I ( l , p , b ) I ( l , p + 2 , b ) ] 2 , p = 2 , 4 , , N p 2 ,
W ( i , j ) = { k [ I ( l , p , b ) I ( l + i , p + j , b + k ) ] 2 } 1 / 2 , k = n b , , 1 , 1 , , n b .
I ( l , p , b ) = i , j I ( l + i , p + j , b ) W C ( i , j ) , i , j = 1 , 0 , 1.
C 2 = ( 0 1 0 0 0 0 0 1 0 ) , C 4 = ( 0 1 0 1 0 1 0 1 0 ) , C 8 = ( 1 1 1 1 0 1 1 1 1 ) .
K = ( 1 1 0 0 ) .
D ( x 1 , x 2 ) = arccos ( x 1 , x 2 / ( x 1 x 2 ) ) ,
θ ( l , p , b ) = p log ( I ( l , p , b ) ) = log ( I ( l , p , b ) ) log ( I ( l , p 1 , b ) ) ,
H ( x , T ) = G H ( T ) H ( x Δ x ( T ) ) ,
H ( p , T ) = p 1 / 2 p + 1 / 2 H ( x , T ) d x .
H 1 ( p binned ) = 1 2 [ H 2 ( p 1 ) + H 2 ( p ) ] ,

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