Adaptive Spatial-Temporal-Spectral Filters for Point Target Detection

In allusion to the problem of dim moving spot target detection in the presence of highly structured background clutter,the authors put forward a new algorithm of adaptive spatial-temporal-spectral multidimensional filter(called ASTS filter) according to the applicable principle of the Wiener-Hopf equations,and present a new algorithm to implement multidimensional information fusion.In this way,there are three processes.Firstly,the quality of inosculate of spatial-temporal-spectral multidimensional information is studied.Secondly,the filter template which in allusion to the moving dim spot target is constructed.Lastly,the Recursive Least Squares(RLS) filter is applied to the multi-spectral infrared images with highly structured background clutter.In general,the gray of pixels will be used as the input parameter of the RLS filter,and the large-size matrix will bring the huge computational load.The spatial-temporal-spectral multidimensional information is used as the input parameter in the new filter,and then it can shun the large-size matrix and reduce the computational load.By the way,the new filter can get the higher output SNR(Signal Noise Ratio).A great deal of experimental data testifies the well performance of this algorithm in filtering.