• DocumentCode
    1535588
  • Title

    JPEG2000 Encoding of Remote Sensing Multispectral Images With No-Data Regions

  • Author

    González-Conejero, Jorge ; Bartrina-Rapesta, Joan ; Serra-Sagristà, Joan

  • Author_Institution
    Dept. of Inf. & Commun. Eng., Univ. Autonoma Barcelona, Cerdanyola del Valles, Spain
  • Volume
    7
  • Issue
    2
  • fYear
    2010
  • fDate
    4/1/2010 12:00:00 AM
  • Firstpage
    251
  • Lastpage
    255
  • Abstract
    Most sensors used for remote sensing (RS) purposes capture more than one component to seize different features from the Earth´s surface. Usually, either multispectral images acquired for RS applications are corrected or the user/application determines valid regions within the image. Consequently, regions without information may emerge ( no-data regions). This letter proposes to encode multispectral images with no-data regions through the JPEG2000 framework, taking into account the lack of importance of these irrelevant regions. Experimental results, performed on data from real scenarios, suggest that the best approach analyzed is the shape-adaptive (SA) Karhunen-Loe??ve transform to decorrelate the spectral redundancy and then the SA multicomponent JPEG2000. The coding-performance improvement over other coding systems considered (Binary Set Splitting with K-D Trees, SA Wavelet Difference Reduction, and SA TARP) is from 5 to 20 dB in signal-to-noise ratio energy.
  • Keywords
    Karhunen-Loeve transforms; geophysical image processing; geophysical techniques; remote sensing; JPEG2000 encoding; K-D trees; SA TARP; SA wavelet difference reduction; binary set splitting; coding-performance improvement; decorrelation transform; no-data regions; remote sensing multispectral images; shape-adaptive Karhunen-Loeve transform; signal-to-noise ratio energy; spectral redundancy; Decorrelation transform; JPEG2000; Karhunen–Loêve transform (KLT); no-data region coding; remote sensing (RS); shape-adaptive (SA);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2009.2032370
  • Filename
    5308311