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Method for detecting spatial weak moving target

A technology for moving targets and detection methods, applied in image data processing, instruments, calculations, etc., can solve the problems of inability to effectively eliminate false targets, insufficient detection rate, and inability to solve the problem of targets being occluded by stars.

Inactive Publication Date: 2011-06-01
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

Since it is necessary to use more than 5 frames of images for accumulation when removing stars, the efficiency of algorithm processing is reduced, and when the background illumination and noise change drastically, multi-frame accumulation cannot enhance the contrast between the target and the stars; after obtaining the candidate target , just use the logic-based nearest neighbor correlation method to correlate the target between two adjacent frames, and do not fully utilize the entire target trajectory information of the sequence image, so it cannot effectively eliminate false targets. When the local signal-to-noise ratio of the target is less than 3 , the detection rate is less than 90%, and it cannot solve the problem that the target is blocked by stars

Method used

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Embodiment Construction

[0027] 1. Single frame image preprocessing.

[0028] After the target and stars are imaged, they appear as star points in the image. Firstly, the star points are segmented, and the image is divided into S×S areas. The grayscale at the maximum value of the graph is used as the background mean value μ of the area, and then iteratively calculates the 3 times the variance 3σ of the background noise, and uses μ+3σ as the segmentation threshold, and performs binarization of 0 and 1 on the small block area according to this threshold deal with. According to the result of binary segmentation, an undirected graph G(V, E) is established, where V is all pixels, and E is the edge between nodes. In the value map, if there are two pixels (x 1 ,y 1 ) and (x 2 ,y 2 ) adjacent, and both pixels are 1 on the binary map, then there is an edge E((x 1 ,y 1 ), (x 2 ,y 2 )), whose weight is 1. After the undirected graph is established, the problem of target connectivity is transformed into ...

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Abstract

The invention discloses a method for detecting a spatial weak moving target, for solving the technical problem that the traditional method for detecting a spatial weak moving target is low in detection ratio. The technical scheme is that a moving target is detected by using a method combining the target track continuity with the characteristics such as target gray level, background constitutive property, and the like; in an image pretreatment stage, the effect of noise is effectively eliminated by cutting based on the gray level and area; in a detection stage, the target moving continuity characteristic between two frames is utilized to effectively eliminate the quasar interference, and the problems that the processing efficiency is decreased by accumulating multiple frames in order to eliminate the quasar and the quasar background cannot be removed under the influence of background illumination and noise are solved; the whole target track is finally treated and the false target is removed; and the lost target is filled. When the signal-to-noise is less than 3, the detection ratio is increased to above 95% from the detection ratio below 90% in the prior art.

Description

technical field [0001] The invention relates to a space target detection method, in particular to a space weak moving target detection method. Background technique [0002] The document "Research on Detection Algorithms of Weak and Small Moving Targets in Deep Space Background, Optical Technology, 2010, Vol36(2), p209-212" discloses a detection algorithm for weak and small moving targets in deep space background based on multi-frame accumulation and feature extraction of sequential images . In this method, the background is suppressed first; the contrast between the target and the star is enhanced by accumulating multiple frames of sequence images, the local star map is extracted and the interference of the star is eliminated; finally, the target detection is completed by combining the characteristics of the candidate target. Since it is necessary to use more than 5 frames of images for accumulation when removing stars, the efficiency of algorithm processing is reduced, and...

Claims

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Application Information

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IPC IPC(8): G06T7/20G06T7/60
Inventor 张艳宁段锋姚睿孙瑾秋施建宇杨涛朱宇张永鹏张臻李磊
Owner NORTHWESTERN POLYTECHNICAL UNIV
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