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Journal of Applied Remote Sensing

JPEG2000 encoding of images with NODATA regions for remote sensing applications
Author(s): Alaitz Zabala; Jorge Gonzalez-Conejero; Joan Serra-Sagrista; Xavier Pons
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Paper Abstract

The aim of this work is to, within the JPEG2000 framework, enhance the coding performance obtained for images that contain regions without useful information, or without information at all, here named as NODATA regions. In Geographic Information Systems (GIS) and in Remote Sensing (RS), NODATA regions arise due to several factors, such as geometric and radiometric corrections, atmospheric events, the overlapping of successive layers of information, etc. Most coding systems are not devised to consider these regions separately from the rest of the image, sometimes causing a loss in the coding efficiency and in the post-processing applications. We propose two approaches that address this issue; the first technique (Average Data Region, ADR) is carried out as simple pre-processing and the second technique (Shape-Adaptive JPEG2000, SA-JPEG2000) modifies the coding system to avoid the regions without information. Experimental results, performed on data from real applications and different scenarios, suggest that the proposed approaches can achieve, e.g., for SA-JPEG2000, a Signal-to- Noise Ratio improvement of about 8 dB. Moreover, in a post-processing application such as a digital classification, the best classification results are obtained when the proposed approaches SA-JPEG2000 and ADR are applied.

Paper Details

Date Published: 1 July 2010
PDF: 19 pages
J. Appl. Rem. Sens. 4(1) 041793 doi: 10.1117/1.3474978
Published in: Journal of Applied Remote Sensing Volume 4, Issue 1
Show Author Affiliations
Alaitz Zabala, Univ. Autònoma de Barcelona (Spain)
Jorge Gonzalez-Conejero, Univ. Autònoma de Barcelona (Spain)
Joan Serra-Sagrista, Univ. Autònoma de Barcelona (Spain)
Xavier Pons, Univ. Autònoma de Barcelona (Spain)

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