Edge feature-based unmanned aerial vehicle image blur judgment method and system

Abstract

The invention relates to an edge feature-based unmanned aerial vehicle image blur judgment method and system. The method includes the following steps of: performing spatial region blur analysis: the edge features of an original image taken by an unmanned aerial vehicle are extracted by using an eight-direction Prewitt algorithm, partitioning processing is performed on the original image, and the number of edges of each block in set four directions is put into statistics, and whether the image is a blurred image is judged according to the number of edge line segments of each block; performing frequency-domain blur analysis: discrete Fourier transformation is performed on the original image, the sharpness index of the power spectrum of the transformed image is analyzed, and whether the image is a blurred image is judged according to the sharpness index; determining whether the image is a clear image or a blurred image; and performing local edge blur analysis: the width of the edges is calculated according to the detected location information of the edge line segments, so that a local blur judgment index can be obtained, and whether the image is a clear image or a blurred image can be determined. The method and system of the invention have the advantages of standardization and standardized image blur detection process, and can improve accuracy and efficiency of detection.

Description

technical field

[0001] The invention belongs to the technical field of image processing, and in particular relates to a method and system for judging the blurring of an unmanned aerial vehicle image based on edge features. Background technique

[0002] With the development of society and economy, in order to meet the increasing demand for electricity, the mileage of transmission lines is increasing year by year, which poses a huge challenge for the daily inspection of lines. In order to meet the needs of inspections and improve inspection efficiency, unmanned aerial vehicles (UAVs) have been introduced into the operation and maintenance of transmission lines as a new inspection mode. UAVs carry visible light image acquisition equipment to collect information on the status of power transmission lines. Due to changes in flight altitude, camera lens out of focus, jitter of UAVs affected by atmospheric turbulence, and noise caused by environmental electromagnetic interference, ...

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