In an earlier conference, we introduced a powerful class of temporal filters, which have outstanding signal to clutter gains in evolving cloud scenes. The basic temporal filter is a zero-mean damped sinusoid, implemented recursively. Our final algorithm, a triple temporal filter, consists of a sequence of tow zero-mean damped sinusoids followed by an exponential averaging filter along with an edge suppression factor. The algorithm was designed, optimized and tested using a real world database. We applied the Simplex algorithm to a representative subset of our database to find an improved set of filter parameters. Analysis led to two improved filters: one dedicated to benign clutter conditions and the other to cloud clutter-dominated scenes. In this paper, we demonstrate how a fused version of the two optimized filters further improves performance in severe cloud clutter scenes. The performance characteristics of the filters will be detailed by specific examples and plots. Real time operation has been demonstrated on laboratory IR cameras.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.