This paper deals with the problem of detection and tracking of point-targets from a sequence of IR images against slowly moving clouds as well as structural background. Many algorithms are reported in the literature for tracking sizeable targets with good result. However, the difficulties in tracking point-targets arise from the fact that they are not easily discernible from point like clutter. Though the point-targets are moving, it is very difficult to detect and track them with reduced false alarm rates, because of the non-stationary of the IR clutter, changing target statistics and sensor motion. The focus of research in this area is to reduce false alarm rate to an acceptable level. In certain situations not detecting a true target is acceptable, but declaring a false target as a true one may not be acceptable. Although, there are many approaches to tackle this problem, no single method works well in all the situations. In this paper, we present a multi-mode algorithm involving scene stabilization using image registration, 2D spatial filtering based on continuous wavelet transform, adaptive threshold, accumulation of the threshold frames and processing of the accumulated frame to get the final target trajectories. It is assumed that most of the targets occupy a couple of pixels. Head-on moving and maneuvering targets are not considered. It has been tested successfully with the available database and the results are presented.