• DocumentCode
    1014965
  • Title

    Restoration of Aqua MODIS Band 6 Using Histogram Matching and Local Least Squares Fitting

  • Author

    Rakwatin, Preesan ; Takeuchi, Wataru ; Yasuoka, Yoshifumi

  • Author_Institution
    Earth Obs. Res. Center, Japan Aerosp. Exploration Agency, Tsukuba
  • Volume
    47
  • Issue
    2
  • fYear
    2009
  • Firstpage
    613
  • Lastpage
    627
  • Abstract
    The MODerate resolution Imaging Spectrometer (MODIS) aboard Terra and Aqua platforms is performing well overall, except for Aqua MODIS band 6. Fifteen of the 20 detectors in Aqua MODIS band 6 are nonfunctional or noisy. Without correction, it will cause problems in the higher MODIS products. This paper develops a restoration algorithm to restore the missing data of Aqua MODIS band 6 by combining a histogram-matching algorithm with local least squares fitting. Histogram matching corrects detector-to-detector striping of the functional detectors. Local least squares fitting restores the missing data of the nonfunctional detector based on a cubic polynomial derived from the relationship between Aqua MODIS bands 6 and 7. The Aqua MODIS image data used in this research are in digital number format and are not georectified. The proposed restoring algorithm can be used on both 1000- and 500-m pixel resolutions. The algorithm was tested on both Terra and Aqua MODIS images. For Terra MODIS images, results of restoring the synthetic nonfunctional detectors of band 6 demonstrate that local least squares fitting can fill in the missing data with little distortion. For Aqua MODIS images, the results of the restoring algorithm with and without applying histogram matching were compared to evaluate the capability in removing detector-to-detector stripe noise. To evaluate the performance of the proposed method, quantitative and qualitative analyses were carried out by visual inspection and quality index. For all the scenes used in this research, the correlation coefficients were near 0.99 and root mean square error between the original Terra band 6 and its simulated one was 2times10-5. The proposed algorithm can thus be used satisfactorily for restoring Aqua MODIS band 6.
  • Keywords
    aerosols; clouds; geophysical techniques; image restoration; least squares approximations; remote sensing; snow; Aqua MODIS band; MODerate resolution Imaging Spectrometer; Terra MODIS images; aerosol product; cloud-mask product; detector-to-detector stripe noise; digital number format; functional detectors; histogram-matching algorithm; local least squares fitting; restoration algorithm; root mean square error; snow cover product; synthetic nonfunctional detectors; Aqua; MODerate resolution Imaging Spectrometer (MODIS); band 6; histogram matching; local least squares fitting;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2008.2003436
  • Filename
    4694066