Abstract
Detection of point objects on a sequence of video images is an important step in optical monitoring systems for UAVs, since they allow them to be detected on the maximum range. This task is quite complicated because the intensity of the object in the image is low due to the low signal / noise ratio (SNR). Decisive statistics of marks are used to increase the effectiveness of object tracking. The paper presents a method for detecting point objects on a video images sequence according to Wald test using distributions of decisive statistics in likelihood ratio. Results of statistical modeling show that the synthesized algorithm reduces the detection time and reduce computational complexity compared with known algorithms detect a moving object IMM-PDAF-AI, which uses the decisive statistics of marks and IMM-PDAF, which does not use decisive statistics of marks.
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