Unmanned aerial vehicle video small-object detecting method based on super-resolution reconstruction

A super-resolution reconstruction and small target detection technology, which is applied in image analysis, image data processing, instruments, etc., can solve the problems of difficult and difficult detection of targets in UAV videos

Active Publication Date: 2016-03-09
XIDIAN UNIV
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method for detecting small targets in UAV video based on super-resolution reconstruction, aiming at solving the problem that the target is too small and difficult to detect in the current UAV video

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  • Unmanned aerial vehicle video small-object detecting method based on super-resolution reconstruction

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Embodiment Construction

[0075] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0076] Image super-resolution reconstruction technology can obtain higher-resolution output images from multiple frames of low-resolution input images. Compared with directly using high-definition imaging equipment, multi-frame super-resolution reconstruction technology belongs to software processing, which is simple to implement, low in cost, and convenient Updated, easy to port. The small target detection method of UAV video based on super-resolution reconstruction can improve the target detection probability and reduce the false alarm probability.

[0077] The application principle of the present invention will be descr...

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Abstract

The invention discloses an unmanned aerial vehicle video small-object detecting method based on super-resolution reconstruction. The unmanned aerial vehicle video small-object detecting method comprises the steps of selecting one input image as a reference frame, and selecting three consecutive image frames for performing sub-pixel displacement estimation on the reference frame; then placing the displacement estimation result of the four image frames into a high-resolution image grid; and estimating pixels which are lost in the high-resolution image grid, thereby obtaining an objective image with a relatively high resolution. Afterwards, an objective template is extracted from the objective image, and the characteristic of the objective image is calculated. Then the reconstructed objective image is divided for obtaining a plurality of objective area blocks. Characteristic extraction and characteristic identification are successively performed on all objective area blocks, thereby finishing preliminary detection for the object. Afterwards, false object elimination is performed, thereby obtaining a final detection result.

Description

technical field [0001] The invention belongs to the technical field of machine vision, image processing and automatic control, can be used for target detection of unmanned aerial vehicle infrared rays, visible light video or images, and has strong advantages in military reconnaissance, remote sensing survey, traffic monitoring, public safety, production line monitoring and other fields. application prospects. Compared with ordinary video target inspection, the UAV video small target detection method based on super-resolution reconstruction can reduce the false alarm probability, increase the inspection probability, and enhance the detection effect. Background technique [0002] Unmanned Aerial Vehicle (UAV, Unmanned Aerial Vehicle) is an unmanned aerial vehicle that is self-powered, carries a variety of equipment, performs multiple tasks, and can be reused. UAVs were mainly used for military tasks at the earliest, including reconnaissance and surveillance, communication rel...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T3/40
CPCG06T3/4007G06T3/4053G06T2207/10016G06T2207/20081
Inventor 宁贝佳张建龙高新波来浩坤
Owner XIDIAN UNIV
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