A multispectral camera concept is presented. The concept is based on using a patterned filter in the focal plane, combined with scanning of the field of view. The filter layout has stripes of different bandpass filters extending orthogonally to the scan direction. The pattern of filter stripes is such that all bands are sampled multiple times, while minimizing the total duration of the sampling of a given scene point. As a consequence, the filter needs only a small part of the area of an image sensor. The remaining area can be used for conventional 2D imaging. A demonstrator camera has been built with six bands in the visible and near infrared, as well as a panchromatic 2D imaging capability. Image recording and reconstruction is demonstrated, but the quality of image reconstruction is expected to be a main challenge for systems based on this concept. An important advantage is that the camera can potentially be made very compact, and also low cost. It is shown that under assumptions that are not unreasonable, the proposed camera concept can be much smaller than a conventional imaging spectrometer. In principle, it can be smaller in volume by a factor on the order of several hundred while collecting the same amount of light per multispectral band. This makes the proposed camera concept very interesting for small airborne platforms and other applications requiring compact spectral imagers.

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Abstract-This article deals with fast and accurate visualization of pushbroom image data from airborne and spaceborne platforms. A pushbroom sensor acquires images in a linescanning fashion, and this results in scattered input data that needs to be resampled onto a uniform grid for geometrically correct visualization. To this end, we model the anisotropic spatial dependence structure caused by the acquisition process. Several methods for scattered data interpolation are then adapted to handle the induced anisotropic metric and compared for the pushbroom image rectification problem. A trick that exploits the semi-ordered line structure of pushbroom data to improve the computational complexity several orders of magnitude is also presented.