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

A technology of edge features and fuzzy judgment, applied in the field of image processing, can solve problems such as long processing time

Active Publication Date: 2017-03-22
STATE GRID INTELLIGENCE TECH CO LTD
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Problems solved by technology

Decompose the image into multiple layers of images, and perform wavelet tran

Method used

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

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Embodiment Construction

[0131] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0132] Such as Figure 4 As shown, the method for judging the ambiguity of UAV images based on edge features includes the following steps:

[0133] Step (1): Spatial domain fuzzy analysis. Use the eight-direction Prewitt algorithm to extract image edge features and analyze the number of line segments in each direction to determine whether the image is blurred;

[0134] Step (2): frequency domain fuzzy analysis. Perform FFT (Fast Fourier Transform) on the image, analyze the sharpness index of the transformed power spectrum, and judge whether the image is blurred;

[0135] Step (3): according to the results of step (1) and step (2), determine the final blur of the image;

[0136] Step (4): Local edge ambiguity analysis. Calculate the width of the edge according to the position information of the detected edge segment, compare it with the local area whe...

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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, ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/13
CPCG06T7/0002G06T2207/20056G06T2207/30168
Inventor 蒋斌刘越王万国刘俍张方正杨波朱德袆慕世友李超英李宗谕李建祥赵金龙李勇吴观斌许乃媛
Owner STATE GRID INTELLIGENCE TECH CO LTD
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