A moving point target detection method based on maximum-time index joint

Abstract

The invention discloses a motor point target detection method based on maximum-time index union. The method comprises the following steps: 1) a maximum gray value projected image and a time index frame image are obtained; 2) noise filtering process is performed on the time index frame image; 3)a motor point target in the time index frame image is detected. The motor point target detection method based on the maximum-time index union can effectively detect the motion trail of dispersed punctiform targets in a sequence image and need no prior information of the targets. The calculated amount is small and the instantaneity is high.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a moving point target detection method based on a maximum value-time index combination. Background technique [0002] The detection, recognition and tracking technology of moving point targets is one of the important contents of moving target recognition in sequence video images. Previous research on sequence image tracking systems mainly focused on the conditions of short distance, large targets, and strong signal-to-noise ratio. Under such conditions, the large target contains rich texture and contour information, and multiple features can be selected for its detection, and the detection and recognition of the target can be carried out on the basis of a single frame. [0003] Due to the long imaging distance of point moving targets, the imaging area of ​​the target on the photodetector is only a few or even one pixel, which appears as a weak point in the sy...

AI Technical Summary

Problems solved by technology

[0005] (2) The contrast between the brightness of the image moving point target and its neighborhood background is low

[0008] (5) The law of target movement is irregular, which makes the search and detection of the target image more difficult

[0009] (6) In the process of target tracking, due to the low signal-to-noise ratio of the target, the algorithm often detects multiple false targets, which affects the performance of the tracking filter

However, the commonly used methods of tracking first and then detecting have shortcomings such as requiring prior information (speed, direction, etc.)

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