Using iterated rational filter banks within the ARSIS concept for producing 10 m Landsat multispectral images

The ARSIS concept is meant to increase the spatial resolution of an image without modification of its spectral contents by merging structures extracted from a higher resolution image of the same scene but in a different spectral band. It makes use of wavelet transforms and multiresolution analysis. It is currently applied in an operational way with dyadic wavelet transforms that limit the merging of images whose ratio of their resolution is a power of two. Nevertheless, provided some conditions, rational discrete wavelet transforms can be numerically approximated by rational filter banks which would enable a more general merging: indeed, in theory, the ratio of the resolution of the images to merge is a power of a certain family of rational numbers. The aim of this article is to examine whether the use of those approximations of rational wavelet transforms are efficient within the ARSIS concept. Producing 10 m Landsat multispectral images 2 This work relies on a particular case: the merging of a 10 m SPOT Panchromatic image and a 30 m Landsat Thematic Mapper multispectral image to synthesize 10 m multispectral image called TM-HR.