Automatic detection of targets from far distances is a very challenging problem. Background clutter and small target size
are the main difficulties which should be solved while reaching a high detection performance as well as a low
computational load. The pre-processing, detection and post-processing approaches are very effective on the final results.
In this study, first of all, various methods in the literature were evaluated separately for each of these stages using the
simulated test scenarios. Then, a full system of detection was constructed among available solutions which resulted in
the best performance in terms of detection. However, although a precision rate as 100% was reached, the recall values
stayed low around 25-45%. Finally, a post-processing method was proposed which increased the recall value while
keeping the precision at 100%. The proposed post-processing method, which is based on local operations, increased the
recall value to 65-95% in all test scenarios.