An image processing technique for simultaneously altering the effective angular response and spatial sampling characteristics of a sampled image

Optical imagers for space-based remote sensing are very expensive to develop. While designing space-qualified imager hardware to meet specific customer requirements can be a stimulating engineering challenge, such developments incur large non-recurring costs associated with designing, qualifying, and testing completely new space imaging hardware. It is often far more cost-effective to use ground image processing to render the data from an existing and well-understood space imager into a data stream that conforms to another set of imaging system requirements rather than developing new hardware to do the new task. This situation can occur when a replacement space-based meteorological imaging system is needed and there is a large user infrastructure that is based on the characteristics of the system to be replaced which would be very expensive and time consuming to change. An image processing approach is presented that is designed to convert the image obtained from an existing GOES-like meteorological imager into one that has different spatial sampling and angular response characteristics which are commensurate with some other space based meteorological imaging systems currently in use