Human visual system (HVS) can detect the target utilizing the contrast of the target and the surrounding background
under a low SNR, it is not only sensitive to the local contrast in space domain, but also in time domain. The existing
infrared small target detection methods based on HVS are mainly based on the local contrast in space domain, while the
false alarm caused by the background clutter could be serious. In consideration of this problem, an infrared small target
detection method based on visual spatio-temporal contrast measure (STLCM) is proposed. At the first stage, a temporal
local contrast measure (TLCM) was presented. At the second stage, visual spatio-temporal contrast measure was derived
by the fusion of the local contrast in time and space domain, then an adaptive threshold was adopted in the saliency map
of STLCM to segment the target. Experimental results demonstrate that the proposed method is superior in compressing
the false alarm and efficient in different conditions.
In order to detect the dim small target in high frame rate image sequences,an optimized temporal processing technique is
investigated. Based on the temporal profile models for noise pixel,target pixel and clutter pixel, we formulate the
detection in two steps, pre-processed by Max-median filter and temporal variance filter(TVF). In pre-processing step,
three spatial-filtering methods are compared. In temporal profile analysis step, the length of time windows for calculating
the mean and variance values are chosen after statistical analysis. Finally, six targets embedded into a scene which
contains different types of clouds, and set the adjacent scene to one pixel jitter in any random direction. The simulation
results show that we can obtain a relative high signal-to-clutter gain in different regions, which satisfies the requirement
of target detection algorithm in high frame rate detection system.
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