An unsupervised target detection method based on prior information and aircraft shape in remote sensing images

Abstract

The invention discloses a remote sensing image unsupervised target detection method based on prior information and aircraft shape, which mainly solves the problems of blind positioning and slow positioning speed of optical remote sensing image target detection in large and complex scenes at present. The invention adopts an unsupervised method for aircraft positioning and accurately positioning. The realization steps are as follows: 1. establishing the initial sketch model for the original drawing and extracting the initial sketch; 2. according to the position relation of the line segments in the sketch map, finding out the sketch line segments which may constitute the wing of the aircraft; 3. from the result of the previous step, the sketch line segment that can compose the symmetrical wing being found; 4. using the information of the sketch map and the line and surface of the original map, the region around the sketch line segment of the symmetrical wing being grown to obtain the surface of the aircraft; 5. the outer rectangular frame being obtained according to the surface area of the aircraft, and the outer contour of the aircraft being obtained at the same time, so that the precise positioning can be realized. Fast positioning of airplane target in optical remote sensing image is realized, which can be used for airplane target recognition and image interpretation in opticalremote sensing image.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an unsupervised target detection method for remote sensing images based on prior information and aircraft shape, which can be used for aircraft target recognition and image interpretation of optical remote sensing images. Background technique [0002] With the development of space remote sensing technology, remote sensing platforms have developed from early airships and airplanes to current satellites and spaceships, and the platforms and methods for people to obtain remote sensing data have greatly improved. There is an increasing amount of high-resolution and large-scale image data in large scenes, but the data processing capability is far lower than the ability to obtain data. Especially for large-scale scenes, in the face of complex and changeable target environments, how to efficiently and accurately detect specific targets, It has always been a very important and u...

AI Technical Summary

Problems solved by technology

[0004] For large and complex scenes with complicated targets, the sparse image after sketching of optical remote sensing images is used, combined with the original image, to make full use of prior information, from line to surface in the picture, and then from surface to area

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