Insulator Hydrophobic Image Edge Detection Algorithm considering Deconvolution and Deblurring Algorithm
In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linea...
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| Published in | Mathematical problems in engineering Vol. 2022; pp. 1 - 12 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Hindawi
23.02.2022
John Wiley & Sons, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1024-123X 1026-7077 1563-5147 1563-5147 |
| DOI | 10.1155/2022/1871079 |
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| Abstract | In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linear summation is used to obtain a stable, multiscale image model representation. This paper extracts the contours of the salient areas of the image and adjusts the parameters of the deconvolution network to learn the salient area patterns of the image. At the same time, for the image to be generated, a shape template is used to limit the range of the area to be generated in order to obtain a shape image with similar patterns. When the spatial relative relationship characteristics of the image constituent objects are obvious, we appropriately add high-level semantic feature activation values for reinforcement. This paper solves the estimation of the unknown blur kernel by using image prior knowledge, filtering and gradient domain algorithms and other different technologies to obtain image jitter or scene movement information and estimate the size, location, and density of the blur kernel. This paper studies a relatively robust deconvolution model, which is insensitive to random noise, has stable effects, and can overcome the water ripple effect caused by the usual convolution process. This paper attempts to study the fuzzy model with variable space. The usual blur is a spatial invariant model; that is, a single kernel is used to describe the motion of all pixels on the image. By selecting different characteristic parameters, this paper conducts experimental research on some existing hydrophobic indicator function methods and calculates the relationship between characteristic parameters and hydrophobicity when different hydrophobic indicator functions are adopted. One characteristic of the hydrophobic image of composite insulators is low contrast. The traditional method of converting color images to grayscale images cannot improve the image contrast. This paper analyzes the hydrophobic image of the composite insulator, and the extracted B channel component image of the hydrophobic image improves the contrast of the image and facilitates the subsequent segmentation of water traces and background. In this paper, the water repellent image's watermark area is counted, and connected-domain wave processing is used to limit the area of water droplets retained, thereby improving the efficiency of filtering water droplets without having a big impact on the image as a whole. The problem of uneven illumination is an unavoidable problem in the field of image processing, and the resulting reflection problem brings difficulties to image processing. This article regards the reflective area of the watermark as a “hole” and uses the idea of “hole filling” to eliminate the reflective point, which weakens the reflection problem to a certain extent. |
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| AbstractList | In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linear summation is used to obtain a stable, multiscale image model representation. This paper extracts the contours of the salient areas of the image and adjusts the parameters of the deconvolution network to learn the salient area patterns of the image. At the same time, for the image to be generated, a shape template is used to limit the range of the area to be generated in order to obtain a shape image with similar patterns. When the spatial relative relationship characteristics of the image constituent objects are obvious, we appropriately add high-level semantic feature activation values for reinforcement. This paper solves the estimation of the unknown blur kernel by using image prior knowledge, filtering and gradient domain algorithms and other different technologies to obtain image jitter or scene movement information and estimate the size, location, and density of the blur kernel. This paper studies a relatively robust deconvolution model, which is insensitive to random noise, has stable effects, and can overcome the water ripple effect caused by the usual convolution process. This paper attempts to study the fuzzy model with variable space. The usual blur is a spatial invariant model; that is, a single kernel is used to describe the motion of all pixels on the image. By selecting different characteristic parameters, this paper conducts experimental research on some existing hydrophobic indicator function methods and calculates the relationship between characteristic parameters and hydrophobicity when different hydrophobic indicator functions are adopted. One characteristic of the hydrophobic image of composite insulators is low contrast. The traditional method of converting color images to grayscale images cannot improve the image contrast. This paper analyzes the hydrophobic image of the composite insulator, and the extracted B channel component image of the hydrophobic image improves the contrast of the image and facilitates the subsequent segmentation of water traces and background. In this paper, the water repellent image's watermark area is counted, and connected-domain wave processing is used to limit the area of water droplets retained, thereby improving the efficiency of filtering water droplets without having a big impact on the image as a whole. The problem of uneven illumination is an unavoidable problem in the field of image processing, and the resulting reflection problem brings difficulties to image processing. This article regards the reflective area of the watermark as a “hole” and uses the idea of “hole filling” to eliminate the reflective point, which weakens the reflection problem to a certain extent. |
| Author | Ma, Lan Wang, Dalei |
| Author_xml | – sequence: 1 givenname: Dalei orcidid: 0000-0002-4081-7424 surname: Wang fullname: Wang, Dalei organization: School of Mechanical and Electronic EngineeringSuzhou UniversityAnhui 234000Chinasuda.edu.cn – sequence: 2 givenname: Lan orcidid: 0000-0003-2468-9917 surname: Ma fullname: Ma, Lan organization: School of Mathematics and StatisticsSuzhou UniversityAnhui 234000Chinasuda.edu.cn |
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| Cites_doi | 10.1109/tpwrd.2020.2995071 10.1109/mim.2021.9400959 10.1016/j.polymertesting.2018.12.011 10.1016/j.jeurceramsoc.2020.09.071 10.1109/access.2019.2954935 10.1016/j.patrec.2018.04.036 10.1007/s00202-017-0634-z 10.1364/oe.424129 10.1109/access.2017.2757030 10.1049/hve.2019.0052 10.1109/TPWRD.2019.2944741 10.1016/j.surfcoat.2019.05.073 10.1002/pen.25610 10.1016/j.epsr.2017.11.009 10.1016/j.apsusc.2017.01.141 10.1007/s10570-018-1768-5 10.1109/cjece.2017.2751623 10.1109/access.2019.2922279 10.1109/access.2018.2874980 10.1016/j.neucom.2018.06.009 10.1021/acsami.0c05666 10.1109/tci.2020.3032671 |
| ContentType | Journal Article |
| Copyright | Copyright © 2022 Dalei Wang and Lan Ma. Copyright © 2022 Dalei Wang and Lan Ma. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Aging Algorithms Color imagery Deconvolution Deep learning Domains Droplets Edge detection Electricity distribution Energy consumption Engineering Fault diagnosis Hydrophobicity Image contrast Image filters Image processing Image segmentation Insulators Kernels Mathematical models Multilayers Parameters Random noise Teaching methods Vibration Water drops Water purification Watermarking Wavelet transforms |
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| Title | Insulator Hydrophobic Image Edge Detection Algorithm considering Deconvolution and Deblurring Algorithm |
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