CN112861817A - Instrument noise image processing method - Google Patents
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Abstract
The invention discloses a method for processing instrument noise images, which comprises the following steps: step 1, dividing a shot image into input images for information extraction and judgment; step 2, performing edge detection on the input image information, if the input image information contains edge details, judging that the input image is not qualified, skipping the judgment of the next input image, and if the input image information does not contain the edge details, extracting an image without the edge information to form an extracted image; step 3, carrying out noise discrimination on the extracted image, and confirming whether the noise type of the extracted image accords with a salt-pepper noise model or a Gaussian noise model; step 4.1, filtering and denoising the salt-pepper noise model by adopting a median filtering algorithm; step 4.2, filtering and denoising the Gaussian noise model by adopting a bilateral filtering algorithm; and 5, inputting the denoised image information into an identification module for intelligent identification of the image information. The invention can realize the noise reduction processing of the polling shot image.
Description
Technical Field
The invention relates to an instrument noise image processing method used in the field of intelligent inspection of a transformer substation.
Background
High quality and timely operation and maintenance are the prerequisites for ensuring safe and reliable operation of the power system. Modern degree of transformer substation is higher and higher nowadays, and the equipment that increases in a large number leads to artifical daily cost of patrolling and examining to increase day by day, and the problem that traditional artifical daily mode of patrolling and examining is prominent just more but not neglected. Once misjudgment and missed judgment occur in daily routing inspection, great economic loss is caused. Along with the rapid development of subjects such as electronic information technology, automation level and precise control, a large amount of monitoring cameras are installed in a transformer substation, but the traditional camera system only transmits images and is mainly used for security and environmental monitoring, and the device inspection work is hardly helped. The large application of the substation inspection automation equipment is the future development trend of substation automatic inspection. The existing substation inspection operation and maintenance equipment is low in intelligent degree, can execute inspection tasks, shoots key positions of inspection equipment and instrument and meter panels, and still needs to read equipment states and instrument and meter indexes manually, so that the efficiency is low. Due to the fact that a large amount of image noise is usually accompanied with the substation instrument image shot by the inspection robot, the application of follow-up intelligent identification of the inspection image is seriously influenced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a meter noise image processing method which can realize the noise reduction processing of the polling shot image.
One technical scheme for achieving the above purpose is as follows: a meter noise image processing method comprises the following steps:
step 1, dividing a shot image into input images for information extraction and judgment;
step 2, performing edge detection on the input image information, if the input image information contains edge details, judging that the input image is not qualified, skipping the judgment of the next input image, and if the input image information does not contain the edge details, extracting an image without the edge information to form an extracted image;
step 3, carrying out noise discrimination on the extracted image, and confirming whether the noise type of the extracted image accords with a salt-pepper noise model or a Gaussian noise model;
step 4.1, filtering and denoising the salt-pepper noise model by adopting a median filtering algorithm;
step 4.2, filtering and denoising the Gaussian noise model by adopting a bilateral filtering algorithm;
and 5, inputting the denoised image information into an identification module for intelligent identification of the image information.
Further, in the step 4.2, the method for denoising by the median filtering algorithm is to set the gray value of each pixel point of the extracted image as the median of the gray values of all pixel points in a certain neighborhood window of the point, and define the following formula:
g(x,y)＝median{f(x-i,y-i)}x,y∈W
wherein g (x, y) and f (x-i, y-i) are single-channel values of the output and input pixels respectively, and W is a two-dimensional sliding window.
Further, the two-dimensional sliding window is rectangular, cross-shaped, circular or rhombic.
According to the instrument noise image processing method, after the image is input, the image is classified into two different noise types, and classification processing is performed by corresponding noise reduction methods, so that the denoising effect of the image is greatly improved.
Drawings
FIG. 1 is a schematic diagram showing various noises generated during the image acquisition process of a transformer substation instrument;
FIG. 2 is a flow chart of a method for processing a noise image of a meter according to the present invention.
Detailed Description
In order to better understand the technical solution of the present invention, the following detailed description is made by specific examples:
through the automatic inspection means, including the fixed point camera and the inspection robot, the instrument and meter of transformer substation is shot to obtain image information, and the image information is a precondition for carrying out follow-up image intelligent identification analysis and intelligent inspection operation and maintenance.
However, the substation instrument image is affected by various factors, and various noises are generated, as shown in fig. 1.
Under the interference of a complex background environment, the acquired image contains a lot of noises, and most of the noises are generated in an image acquisition process, a system imaging process and a signal transmission process. If the forming factors of the noises can be accurately analyzed, the influence of the noises can be purposefully eliminated. Wherein, speckle noise is generated by the transmission of electric signals in the sensor, and the speckle noise is filtered and filtered by a structural tuple with multi-azimuth function to carry out morphological filtering; shot noise is introduced by a CCD industrial camera when an acquired image is imaged; the hardware components of the camera may also contribute to thermal noise or fixed pattern noise. The several noises often introduced in industrial production environments described above are roughly distributed according to two kinds of noises, namely gaussian noise and salt and pepper noise: the modeling of thermal noise and the like can adopt a Gaussian model; modeling of speckle noise, etc. may employ a model of salt and pepper noise. Therefore, according to different classification processing of noise, the denoising effect is improved.
Referring to fig. 2, a method for processing a noise image of a meter according to the present invention includes the following steps:
step 1, dividing the shot image into input images for information extraction and judgment.
And 2, performing edge detection on the input image information, if the input image information contains edge details, judging that the input image is not qualified, skipping judgment of the next input image, and if the input image information does not contain the edge details, extracting an image without the edge information to form an extracted image.
And 3, carrying out noise discrimination on the extracted image, and confirming whether the noise type of the extracted image accords with a salt-pepper noise model or a Gaussian noise model.
And 4.1, filtering and denoising the salt-pepper noise model by adopting a median filtering algorithm. The method for denoising by the median filtering algorithm is that the gray value of each pixel point of the extracted image is set as the median of the gray values of all pixel points in a certain neighborhood window of the point, and the median is defined as the following formula:
g(x,y)＝median{f(x-i,y-i)}x,y∈W
wherein g (x, y) and f (x-i, y-i) are single-channel values of the output and input pixels respectively, and W is a two-dimensional sliding window. By using different two-dimensional sliding windows, different filtering effects can be achieved. Common two-position sliding windows are rectangular, cross-shaped, circular and diamond-shaped.
And 4.2, filtering and denoising the Gaussian noise model by adopting a bilateral filtering algorithm. The gaussian filtering is a linear smooth filtering, is suitable for eliminating gaussian noise, and is widely applied to a noise reduction process of image processing. The main method of gaussian filtering is to convolve the image with a gaussian kernel.
And 5, inputting the denoised image information into an identification module for intelligent identification of the image information.
It should be understood by those skilled in the art that the above embodiments are only for illustrating the present invention and are not to be used as a limitation of the present invention, and that changes and modifications to the above described embodiments are within the scope of the claims of the present invention as long as they are within the spirit and scope of the present invention.
Claims (3)
1. A meter noise image processing method is characterized by comprising the following steps:
step 1, dividing a shot image into input images for information extraction and judgment;
step 2, performing edge detection on the input image information, if the input image information contains edge details, judging that the input image is not qualified, skipping the judgment of the next input image, and if the input image information does not contain the edge details, extracting an image without the edge information to form an extracted image;
step 3, carrying out noise discrimination on the extracted image, and confirming whether the noise type of the extracted image accords with a salt-pepper noise model or a Gaussian noise model;
step 4.1, filtering and denoising the salt-pepper noise model by adopting a median filtering algorithm;
step 4.2, filtering and denoising the Gaussian noise model by adopting a bilateral filtering algorithm;
and 5, inputting the denoised image information into an identification module for intelligent identification of the image information.
2. The method of claim 1, wherein in step 4.2, the median filtering algorithm is used to perform denoising, in which the gray-level value of each pixel in the extracted image is set as the median of the gray-level values of all pixels in a neighborhood window of the pixel, and the formula is defined as follows:
g(x,y)＝median{f(x-i,y-i)}x,y∈W
wherein g (x, y) and f (x-i, y-i) are single-channel values of the output and input pixels respectively, and W is a two-dimensional sliding window.
3. The instrument noise image processing method according to claim 2, wherein said two-dimensional sliding window is rectangular, cross-shaped, circular or diamond-shaped.
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Cited By (1)
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Application publication date: 20210528 |