Paper
30 December 1994 New merging method of multispectral and panchromatic SPOT images for vegetation mapping
Bruno Garguet-Duport, Jacky Girel, Jean-Marc Chassery, Guy Pautou
Author Affiliations +
Abstract
The French satellite SPOT is carrying two high resolution sensors. The first supplies 10-m panchromatic (0.51-0.73) data; the second supplies multispectral 20-m data (XS1 in the blue band 0.50 - 0.59, XS2 in the green band 0.61 - 0.69, XS3 in the near infra-red band 0.79 - 0.90). The multispectral and panchromatic merging processes are becoming current procedures for studying land covers and particularly for vegetation mapping which needs a good spatial resolution and a good spectral resolution respectively. The usually applied merging methods are more or less altering radiometric values of the original XS data. Original information is modified and, consequently, photointerpretation procedures are becoming awkward or really impossible so a new merging method has been performed. Thanks to the combined panchromatic image, this method is simulating 10-m images while conserving spectral properties of original XS 20-m images. This method uses two tools coming from the signal processing field and based on solid mathematical procedures: the multiresolution analysis and the wavelet transform. The results issued from this merging method are really promising. Analyses and thematic processings (i. e. production of thematic colour composite images) carried out from that high resolution data, have exhibited a significant improvement of imagery added to a great potential concerning vegetation mapping of the floodplains.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bruno Garguet-Duport, Jacky Girel, Jean-Marc Chassery, and Guy Pautou "New merging method of multispectral and panchromatic SPOT images for vegetation mapping", Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); https://doi.org/10.1117/12.196763
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KEYWORDS
Wavelets

Spatial resolution

Image resolution

Vegetation

Wavelet transforms

Spectral resolution

Associative arrays

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