This paper describes methods for fusing multispectral, low-resolution, remotely sensed images with more highly resolved, panchromatic images. The goal is to obtain a high-resolution, multispectral image that combines the spectral characteristic of the low-resolution data with the spatial resolution of the panchromatic image. Unlike other applications, such as image fusion in military missions or computer-aided quality control, the main constraint in remote sensing is the preservation of spectral information for tasks like classification of ground cover.

The second part of the paper demonstrates a technique that cuts the requirement of an additional, more highly resolved panchromatic image out of the process. The method is based on a sub-pixel misalignment of simultaneously acquired spectral bands and uses the displacement as additional information that effectively increases the sampling frequency.

Finally, an example is provided: the depicted fusion algorithms are applied to three related multispectral images of a SPOT (Systeme Probatoire d’Observation de la Terre) satellite scene and the results are compared.