Adaptive reduction of striping for improved sea surface temperature imagery from Suomi National Polar-Orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS)

Journal of Atmospheric and Oceanic Technology

Volumn 31, Issue 1, 2014, Pages 150-163

  Bouali, Marouan ^a,b   Ignatov, Alexander ^b  

^a NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^b Department of Environmental and Radiological Health Sciences   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM PERFORMANCE; DOWNSTREAM APPLICATIONS; ENVIRONMENTAL SATELLITES; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; PROGRAM SPECIFICATION; SEA SURFACE TEMPERATURE IMAGERY; THERMAL EMISSIVE BANDS; VISIBLE INFRARED IMAGING RADIOMETER SUITES;

ADAPTIVE ALGORITHMS; INFORMATION SERVICES; INFRARED IMAGING; RADIOMETERS; SATELLITE IMAGERY; SENSORS;

OCEANOGRAPHY;

ALGORITHM; IMAGERY; RADIOMETER; REMOTE SENSING; SEA SURFACE TEMPERATURE;

EID: 84892475009     PISSN: 07390572     EISSN: 15200426     Source Type: Journal    
DOI: 10.1175/JTECH-D-13-00035.1     Document Type: Article

References (38)

1. Antonelli, P., M. D. Bisceglie, R. Episcopo, and C. Galdi, 2004: Destriping MODIS data using IFOV overlapping. 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 7, IEEE, 4568-4571.
2. Belkin, I. M., and P. C. Cornillon, 2005: Bering Sea thermal fronts from Pathfinder data: Seasonal and interannual variability. Pac. Oceanogr., 3, 6-20.
3. Bhat, P., B. Curless,M. Cohen, and L.Zitnick, 2008: Fourier analysis of the 2D screened Poisson equation for gradient domain problems. Computer Vision-ECCV 2008: 10th European Conference on Computer Vision; Part II, D. Forsyth, P. Torr, and A. Zisserman, Eds., Lecture Notes in Computer Science, Vol. 5303, Springer, 114-128.
4. Bisceglie, M. D., R. Episcopo, C. Galdi, and S. L. Ullo, 2009: Destriping MODIS data using overlapping field-of-view method. IEEE Trans. Geosci. Remote Sens., 47, 637-651.
5. Bouali, M., 2010: A simple and robust destriping algorithm for imaging spectrometers: Application toMODIS data. American Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies, Vol. 1, American Society for Photogrammetry and Remote Sensing, 84-93.
6. Bouali, M., and S. Ladjal, 2010: A variational approach for the destriping of MODIS data. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2194-2197.
7. Bouali, M., and S. Ladjal, 2011: Towards optimal destriping of MODIS data using a unidirectional variational model. IEEE Trans. Geosci. Remote Sens., 49, 2924-2935.
8. Bouali, M., and A. Ignatov, 2012a:Acomparative study of stripe noise on MODIS and VIIRS thermal emissive bands. Earth Observing Systems XVII, J. J. Butler, X. Xiong, and X. Gu, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 8510), doi:10.1117/12.928864.
9. Bouali, M., and A. Ignatov, 2012b: Estimation of detector biases in MODIS thermal emissive bands. IEEE Trans. Geosci. Remote Sens., 51, 4339-4348.
10. Brisson, A., P. L. Borgne, and A. Marsouin, 2002: Results of one year of preoperational production of sea surface temperature from GOES-8. J. Atmos. Oceanic Technol., 19, 1638-1652.
11. Buades, A., B. Coll, and J. M. Morel, 1995: A review of image denoising algorithms, with a new one. MultiscaleModel. Simul., 4, 490-530.
12. Cao, C., F. D. Luccia,X. Xiong, R. Wolfe, and F. Weng, 2013: Early on-orbit performance of the Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. IEEE Trans. Geosci. Remote Sens., doi:10.1109/TGRS.2013.2247768, in press.
13. Chen, J. S., Y. Shao, H. D. Guo, W. Wang, and B. Zhu, 2003: Destriping CMODIS data by power filtering. IEEE Trans. Geosci. Remote Sens., 41, 2119-2124.
14. Corsini, G., M. Diani, and T. Walzel, 2000: Striping removal in MOS-B data. IEEE Trans. Geosci. Remote Sens., 38, 1439- 1446.
15. Crippen, R. E., 1989: A simple spatial filtering routine for the cosmetic removal of scan-line noise from Landsat TM P-tape imagery. Photogramm. Eng. Remote Sens., 55, 327-331.
16. Frankot, R., and R. Chellappa, 1988: A method for enforcing integrability in shape from shading algorithms. IEEE Trans. Pattern Anal. Mach. Intell., 10, 439-451.
17. Franz, B., 1998: A simple destriping algorithm for MOS images. Proceedings of the Second International Workshop on MOSIRS and Ocean Colour, Wissenschaft und Technik Verlag, 297-302.
18. Gadallah, F. L., and F. Csillag, 2000: Destriping multidetector imagery with moment matching. Int. J. Remote Sens., 21, 2505- 2511.
19. Horn, B. K. P., and R. J. Woodham, 1979: Destriping Landsat MSS images by histogram modification. Comput. Graphics Image Process., 10, 69-83.
20. Kahru, M., E. D. Lorenzo, M. Manzano-Sarabia, and B. Mitchell, 2012: Spatial and temporal statistics of sea surface temperature and chlorophyll fronts in the California current. J. Plankton Res., 34, 749-760.
21. LaCasse, K., E. Splitt, S. Lazarus, and W. Lapenta, 2008: The impact of high-resolution sea surface temperatures on the simulated nocturnal Florida marine boundary layer. Mon. Wea. Rev., 136, 1349-1372.
22. Lee, J.-S., 1983: Digital image smoothing and the sigma filter. Comput. Vision Graphics Image Process., 24, 255-269.
23. Lyon, P. E., 2009: An automated de-striping algorithm for Ocean Colour Monitor imagery. Int. J. Remote Sens., 30, 1493-1502.
24. Merchant, C., P. L. Borgne, H. Rocquet, and G. Legendre, 2013: Extended optimal estimation techniques for sea surface temperature from the Spinning Enhanced Visible and Infra- Red Imager (SEVIRI). Remote. Sens. Environ., 131, 287- 297.
25. Pan, J. J., and C. I. Chang, 1992: Destriping of Landsat MSS images by filtering techniques. Photogramm. Eng. Remote Sens., 58, 1417-1423.
26. Rudin, L., S. Osher, and E. Fatemi, 1992: Nonlinear total variation based noise removal algorithms. Physica D, 60, 259-268.
27. Simpson, J. J., J. I. Gobat, and R. Frouin, 1995: Improved destriping of GOES images using finite impulse response filters. Remote Sens. Environ., 52, 15-35.
28. Simpson, J. J., J. R. Stitt, and D. M. Leath, 1998: Improved finite impulse response filters for enhanced destriping of geostationary satellite data. Remote Sens. Environ., 66, 235-249.
29. Smith, S. M., and J. M. Brady, 1995: SUSAN-A new approach to low level image processing. Int. J. Comput. Vision, 23, 45-78.
30. Srinivasan, R., M. Cannon, and J. White, 1988: Landsat data destriping using power spectral filtering. Opt. Eng., 27, 939-943, doi:10.1117/12.7976791.
31. Tadmor, E., S. Nezzar, and L. Vese, 2004: A multiscale image representation using hierarchical (BV, L2) decompositions. Multiscale Model. Simul., 2, 554-579.
32. Tendero, Y., and J. Gilles, 2012: ADMIRE: A locally adaptive single-image non-uniformity correction and denoising algorithm; Application to uncooled IR camera. Infrared Technology and Applications XXXVIII, B. F. Andresen, G. F. Fulop, and P. R. Norton, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 8353), doi:10.1117/12.912966.
33. Torres, J., and S. O. Infante, 2001: Wavelet analysis for the elimination of striping noise in satellite images. Opt. Eng., 40, 1309- 1314.
34. Wegener, M., 1990: Destriping multiple detector imagery by improved histogram matching. Int. J. Remote Sens., 11, 859-875.
35. Weinreb, M. P., R. Xie, J. H. Lienesch, and D. S. Crosby, 1989: Destriping GOES images by matching empirical distribution functions. Remote Sens. Environ., 29, 185-195.
36. Yang, Z., J. Li, W. P. Menzel, and R. A. Frey, 2003: Destriping for MODIS data via wavelet shrinkage. Applications with Weather Satellites, W. P. Menzel et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 4895), 187-199.
37. Yaroslavsky, L. P., 1987: Digital Picture Processing: An Introduction. Springer-Verlag, 276 pp.
38. Zavody, A., C. Mutlow, and D. Llewellyn-Jones, 1995: A radiative transfer model for sea surface temperature retrieval for the along-track scanning radiometer. J. Geophys. Res., 100, 937-952.