Aimed at the imaging principle and characteristic of infrared and visual equipment and their application demands,
an effective algorithm is proposed for small moving target detection based on fused infrared and visual image. The
algorithm suppresses background clutter by morphologic Top-hat transform, and the results are enhanced by
tree-structure wavelet transform with the use of improved fusion rule based on "absolute value" matching degree.
Filter processing can enhance targets as well as suppress partial clutter and false targets effectively. Use difference
operation among three consecutive frame images to accomplish target segmentation. Improve SNR by N frames
energy accumulation. Combine continuity and regularity of small moving target to eliminate false targets, noise
point and background remnant. All that helps detect the small targets. Finally, compare the pre-processing
performance among traditional filter approaches and this proposed algorithm for image pre-processing. Thus, for
this type of method, detection and tracking results prove the validity the proposed algorithm. At the same time, two
parameters, RMSE (relative mean square error) and BSF (background suppression factor), are given to evaluate the
filtering performance of this paper approach. Four indexes, Mutual Information (MI), Associated Entropy (AE),
SNR, RMSE, are used to evaluate the fusion quality. Experimental results show that the multilevel and
multifunctional algorithm proposed is better than other methods in image pre-processing, image fusion and small
moving target detection.