Dim and Small Targets Detection in Sequence Images Based on Spatiotemporal Motion Characteristics
Algorithgm 1
Pseudocode of detection algorithm
Initialization: The constant k in diffusion function is k = 100; The step size between two pixels is step = 4; Enhanced cumulative frames ; Accumulated frames in time domain ; The radius of neighborhood r = 3; Target occurrence threshold ; Threshold of target displacement times ; The sum threshold of target cumulative area .
Input: Original images
(1) Using the improved anisotropy to filter the image with spatial information to obtain the difference image . Then, the direction energy correlation enhancement algorithm is used to realize the energy enhancement in the time domain and obtain the enhanced image .
(2) The segmentation algorithm of reference [25] was used to segment the enhanced image to obtain a sequence binary image.
(3) Combined with formula (7), dim and small targets detection in sequence image with local motion characteristics is used to calculate the number of target occurrence , number of target displacement and the sum of target cumulative area on consecutive frames images. If the conditions are met, it is determined as the target point, and updated the frames images until all the images are processed;
