Background suppression method and system based on neighborhood structures

Abstract

The invention discloses a background suppression method and system based on neighborhood structures. The realization of the method includes: obtaining structure vectors on the basis of gray-scale values of neighborhood pixel points, calculating similarity measures of the structure vectors and neighborhood structure templates, dividing the neighborhood structure templates into a target template and background templates, and utilizing the similarity measures to obtain a background likelihood value of being a background point by an pixel point and a target likelihood value of being a target point by the pixel point; determining the pixel point as the target point if the ratio of the target likelihood value to the background likelihood value is greater than or equal to a threshold value, and otherwise, determining the pixel point as the background point; and using a gray-scale mean value of the background points in a neighborhood pixel point set as an estimated background value, carrying out direct suppression if the pixel point is the background point, and subtracting the estimated background value from a gray-scale value of the target point for background suppression if the pixel point is the target point. The method has a good suppression effect and self-adaptability for different background types, and satisfies real-time calculation requirements at the same time.

Description

technical field [0001] The invention belongs to the field of image processing, and more specifically, relates to a method and system for background suppression based on a neighborhood structure. Background technique [0002] The rapid development of infrared technology makes it widely used in military and civilian fields, and plays an important role in precision guidance, early warning monitoring, optical remote sensing, night navigation and other fields. The detection and tracking of small infrared targets has always been a research hotspot at home and abroad. Small and weak infrared targets at long distances are easily lost in the complex background and difficult to be detected. [0003] The current small target detection is mainly divided into two categories: space domain and time domain. The time domain algorithm can often achieve better results due to the multi-frame information. Accurate to eliminate background motion clutter, resulting in complex algorithms and large...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the above defects or improvement needs of the prior art, the present invention provides a background suppression method and system based on the neighborhood structure, thereby solving the problems in the prior art that it is difficult to simultaneously have a good suppression effect and adapt to different background types Technical issues of performance and real-time computing requirements

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