Underwater image real-time enhancement method based on conditional generative adversarial network

A conditional generation and underwater image technology, applied in the field of image processing, can solve the problems of underwater image noise, distortion, etc., and achieve the effect of improving the enhancement ability

Active Publication Date: 2020-04-24
NANJING INST OF TECH
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Problems solved by technology

[0009] The purpose of the present invention is to provide a real-time enhancement method of underwater images based on con

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  • Underwater image real-time enhancement method based on conditional generative adversarial network
  • Underwater image real-time enhancement method based on conditional generative adversarial network
  • Underwater image real-time enhancement method based on conditional generative adversarial network

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Embodiment Construction

[0041] Such as Figure 1-Figure 4 A real-time enhancement method for underwater images based on a conditional generation confrontation network is shown, including the following steps:

[0042] Step 1: Establish a conditional generative confrontation network system in the robot vision system. The conditional generative confrontation network system includes an image acquisition module, a domain module, a network model module and a discriminator module;

[0043] The image acquisition module is used to obtain the original image, and the domain module is used to input the source domain X and output the expected domain Y on the original image, the source domain X is the distorted image area in the original image, and the expected domain Y is the enhanced image; The goal of the present invention is to learn the mapping G:X→Y to perform automatic image enhancement.

[0044] The present invention adopts a model based on conditional generative adversarial networks, in which the generat...

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Abstract

The invention discloses an underwater image real-time enhancement method based on a conditional generative adversarial network. The invention belongs to the technical field of image processing, the method comprises the steps of establishing a conditional generative adversarial network system in a robot vision system, an image model network is established by following the principle of U-net; establishing a generative adversarial network architecture by adopting a Markov data chain through a discriminator module; the technical problems of noise and distortion of the underwater image are solved;the generative adversarial network is optimized by using a deep convolution method; the visual image enhancement capability of the underwater robot is improved; according to the underwater robot imageenhancement method based on the deep convolution generative adversarial network, the perception quality of the image is evaluated based on the overall content, color, local texture and style information of the image, and a multi-modal target function is formulated to train the model.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a real-time underwater image enhancement method based on a conditional generation confrontation network. Background technique [0002] Autonomous underwater robots are widely used in marine environment monitoring, submarine cable inspection, underwater scene analysis, and submarine topographic mapping. An important problem encountered in the work of underwater robots is that the robot vision system will be seriously affected by low visibility, light refraction, absorption and scattering, and these optical artifacts will cause nonlinear distortion in the captured image, seriously affecting the underwater based Performance of robotic vision systems such as underwater object tracking, detection and classification, segmentation and visual servoing. Fast and accurate image enhancement techniques can alleviate these problems by restoring the perceptual and statistical propertie...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/08G06N3/04
CPCG06T5/002G06T5/007G06N3/088G06T2207/20081G06T2207/20084G06T2207/30181G06N3/045
Inventor 陈巍陈丝雨陈国军
Owner NANJING INST OF TECH
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