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Super-resolution deblurring method of a generated antagonistic network

A super-resolution and deblurring technology, applied in the field of pattern recognition, can solve problems such as low intelligence and poor adaptability, and achieve the effects of improving training speed, reducing impact, and speeding up processing speed

Active Publication Date: 2019-02-22
STATE GRID INTELLIGENCE TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a super-resolution deblurring method of a generative adversarial network, which aims to solve the problems of low intelligence and poor adaptability of the existing deblurring algorithms, and realize the improvement of training speed and deblurring speed. Reducing the Influence of Expertise and Experience on the Design of Deblurring Algorithms

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  • Super-resolution deblurring method of a generated antagonistic network
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  • Super-resolution deblurring method of a generated antagonistic network

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Embodiment Construction

[0033] In order to clearly illustrate the technical features of the present solution, the present invention will be described in detail below through specific implementation methods and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and / or letters in different instances. This repetition is for the purpose of simplicity and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted herein to avoid unnecessarily lim...

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Abstract

The invention provides a super-resolution deblurring method of a generated antagonistic network, which comprises the following steps: S1, utilizing a DRCN network structure to form a super-resolutiondepth convolution network, and establishing an antagonistic network model; S2, combining the SRGAN network cost function to improve the countermeasure network performance; S3, selecting clear picture,adding Gaussian noise and motion blur to realize training. The present invention analyzes the characteristics of motion blur, Designing the artificial noise of samples, adding defocus fuzzy kernel and multi-direction motion fuzzy kernel, realizing the super-resolution deblurring of the blurred image with double magnification, and analyzing the blurred image taken by UAV, can greatly reduce the influence of professional knowledge and experience on the design of deblurring algorithm.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a super-resolution defuzzification method of a generative confrontation network. Background technique [0002] With the rapid development of the economy, the demand for power transmission and transformation in my country continues to increase, the scale of the power system continues to expand, and the safety and stability of the power system are becoming increasingly prominent, which puts forward higher requirements for the reliability of power transmission and transformation technology. The main function of power transmission and transformation technology is to meet people's power needs. At the same time, the skilled application of power technology is also the basis for ensuring stable power supply of the power grid. At the same time, it can effectively prevent accidents during the power supply process and promote the construction and development of my country's power...

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Application Information

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IPC IPC(8): G06T5/00G06N3/04
CPCG06N3/045G06T5/73
Inventor 刘广秀许玮王万国李建祥郭锐赵金龙王振利张旭刘越李振宇刘斌许荣浩白万建李勇杨波孙晓斌
Owner STATE GRID INTELLIGENCE TECH CO LTD
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