@inproceedings {595,
	title = {Efficient interpolation of large image sequences},
	booktitle = {IEEE International Geoscience And Remote Sensing Symposium},
	year = {2002},
	address = {Toronto},
	abstract = {<p>Dynamic estimation of large-scale remote-sensing image sequences is important in a variety of scientific applications. However, the growing size of such sensed images makes conventional dynamic estimation methods, for example the Kalman and related filters, impractical. In this paper we present an approach that emulates the Kalman filter, but with considerably reduced computational and storage requirements. Our approach is illustrated in the context of a large (512 times;512) image sequence of ocean surface temperature.</p>
},
	keywords = {dynamic estimation, geophysical signal processing, image sequences, interpolation, Kalman filter, Kalman filters, large image sequences, large-scale remote-sensing image sequences, ocean surface temperature, oceanographic techniques, Remote Sensing},
	doi = {http://dx.doi.org/10.1109/IGARSS.2002.1027173},
	author = {F M. Khellah and P Fieguth}
}
