Small target detection method based on multi-frame differential image accumulation

Abstract

The invention relates to a small target detection method based on multi-frame differential image accumulation. The method comprises the steps of S1, obtaining and keeping a standard background image ; S2, acquiring multiple frames of images to be detected; S3, respectively carrying out differential operation on each frame of image to be detected obtained in the S2 and the standard background image to obtain a differential image; S4, accumulating the differential images obtained in the S3; and S5, judging whether a to-be-detected target appears or not according to a differential accumulation result; if the to-be-detected target appears, ending the detection; and otherwise, accumulating the multiple frames of to-be-detected image sequences obtained in the step S2 to obtain an average value, taking the average value as a new standard background image and returning to the step S2. According to the method, influence of random noise on differential calculation can be effectively avoided, the difference between the target and the background is enhanced, the separation of the target and the background is further realized, and the target detection can be more accurately realized. Compared with the existing method, the method provided by the invention has higher detection sensitivity and accuracy in an application scene in which the target hovers and is close to the background gray scale.

Description

technical field [0001] The invention relates to the technical field of optical imaging, in particular to a small target detection method based on multi-frame differential image accumulation. Background technique [0002] The use of optical imaging equipment for target detection and tracking has important practical value in the UAV detection neighborhood, but limited by the contradiction between the target resolution and field of view of optical imaging equipment, general optical imaging equipment tends to use large The field-of-view imaging equipment first images a large-scale area, and performs target detection on the obtained image. When there is a potential target in the image, it drives a high-resolution small field-of-view imaging system to focus on the potential target area. Therefore, detecting potential targets from images imaged in a large field of view plays a vital role in whether the optical imaging system can work properly. Since the resolution of the target in...

AI Technical Summary

Problems solved by technology

[0004] However, when a target such as a drone hovers in a low-altitude area, it is very likely that the target itself does not have motion characteristics. At this time, the detection effect of the traditional detection method based on motion saliency will be greatly affected

[0005] When using gray-scale saliency for target detection, if the target and background colors are relatively close, the gray-scale saliency representation is not obvious at this time, and it is difficult to achieve target detection by saliency detection methods such as spectral residual method or maximum inter-class variance method.

Images