An unsupervised object detection method for remote sensing images based on prior information and aircraft shape

Abstract

The invention discloses an unsupervised target detection method for remote sensing images based on prior information and aircraft shape, which mainly solves the problems of blind positioning and slow positioning speed in the current optical remote sensing image target detection of large and complex scenes. positioning, and precise positioning. The implementation steps are: 1. Establish an initial sketch model for the original image, and extract the initial sketch; 2. Find out the sketch line segments that may form the wings of the aircraft according to the positional relationship between the line segments in the sketch; 3. From the results of the previous step Find the sketch line segment that can form the symmetrical wing. 4. Using the line and surface information of the sketch and the original picture, the region grows from the sketch line segment of the symmetrical wing to obtain the aircraft surface; 5. According to the obtained aircraft surface area, the circumscribed rectangular frame can be obtained, and the periphery of the aircraft can be obtained at the same time Contour lines for precise positioning. The rapid positioning of aircraft targets in optical remote sensing images is realized, and it can be used for aircraft target recognition and image interpretation in optical remote sensing images.

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, mainly to solve the current problem of large and complex scenes The problem of blind positioning and slow positioning speed of optical remote sensing image target detection, the present invention adopts an unsupervised method for aircraft positioning, and accurately locates

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