Fusion of high spatial and spectral resolution images: The ARSIS concept and its implementation

In various applications of remote sensing, when high spatial resolution is required in addition with classification results, sensor fusion is a solution. From a set of images with different spatial and spectral resolutions, the aim is to synthesize images with the highest spatial resolution available in the set and with an appropriate spectral content. Several sensor fusion methods exist; most of them improve the spatial resolution but provide poor quality of the spectral content of the resulting image. Based on a multiresolution modeling of the information, the ARSIS concept (from its French name "Amelioration de lu Resolution Spatiale par Injection de Structures") was designed with the aim of improving the spatial resolution together with a high quality in the spectral content of the synthesized images. The general case for the application of this concept is described. A quantitative comparison of all presented methods is achieved for a SPOT image. Another example of the fusion of SPOT XS (20-m) and KVR-1000 (2-m) images is given. Practical information for the implementation of the wavelet transform, the multiresolution analysis, and the ARSIS concept by practitioners is given with particular relevance to SPOT and Landsat imagery.