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Method for intelligently detecting scene video noise of transformer station

A technology for video noise and intelligent detection, applied in image data processing, instrumentation, calculation, etc., can solve problems such as inaccurate detection results

Inactive Publication Date: 2017-03-22
CHINA SOUTHERN POWER GRID COMPANY
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0003] However, the existing video noise detection methods have the disadvantage that the detection results are not accurate enough

Method used

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  • Method for intelligently detecting scene video noise of transformer station
  • Method for intelligently detecting scene video noise of transformer station

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Embodiment Construction

[0040] The present invention will be further described below in conjunction with specific examples.

[0041] The video noise intelligent detection method embodiment of the present invention comprises the following steps:

[0042] The first step: obtain the original code stream of the analog camera and network camera in the substation, and transmit the original code stream to the noise detection device through the RPU (station processing unit); the noise detection device performs video decoding on the obtained original code stream, According to the YUV420 standard, Y, U, V data are obtained respectively;

[0043] Step 2: Obtain two frames of images before and after in the code stream, and respectively perform difference on the Y, U, and V data of the two frames of images: from the three dimensions of color reproduction, peak signal-to-noise ratio, and mean square error signal-to-noise ratio;

[0044] Color rendition: The color rendition is used to evaluate the camera's ability...

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Abstract

A method for intelligently detecting scene video noise of a transformer station includes the steps of S1, obtaining the original code stream of the scene video of the transformer station, and carrying out video decoding to obtain YUV420 standard Y, U, V data, S2, obtaining images of front and rear frames in the code stream, differentiating the Y, U, V data of the current frame image with those of the previous frame image to obtain a foreground image including noise information, S3, calculating a Y data Canny graph of a YUV420 image, conducting expansion processing for the Canny graph, filtering current foreground region according to the graph, conducting convolution operation by using the Laplacian operator with the operator formula being shown in the description to obtain a noise area, converting the texture information of the noise region into SIFT characteristics according to the texture information of the noise region, screening out a candidate region by using a RANSAC algorithm, calculating the noise values on the region by using noise confidence, and S4, outputting the result. The detection result is high in accuracy.

Description

technical field [0001] The invention relates to an intelligent detection method of video noise, in particular to an intelligent detection method of video noise in a substation scene. Background technique [0002] When shooting, the distortion of the optical system or the image blurring and image quality degradation caused by hardware equipment during the transmission process can be regarded as caused by video noise. Reasonably estimating the noise area and performing noise reduction are important means to restore image quality. Video noise intelligent detection is to analyze the video noise level directly based on the video image features, which can simulate human visual characteristics and replace the video fault inspection work done manually in the past. [0003] However, the existing video noise detection methods have the disadvantage that the detection results are not accurate enough. Contents of the invention [0004] The technical problem to be solved by the presen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/30G06T5/50G06T7/13
CPCG06T5/30G06T5/50G06T2207/10016G06T5/70
Inventor 陶文伟胡荣张喜铭樊腾飞李金何锡祺赵旋宇
Owner CHINA SOUTHERN POWER GRID COMPANY
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