Industrial monitoring video image sharpening method based on GAN network

A technology for monitoring video and video images, applied in the field of computer vision, can solve problems such as blurred monitoring video, achieve the effect of small model, high computing efficiency, and simple training process

Active Publication Date: 2020-01-07
XIAN UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a method for clearing industrial monitoring video images based on GAN network, to solve the problems in industrial monitoring Due to dust, smog, and light changes, the monitoring video is blurred, the light is too strong or too dark, and the picture is not clear, such as pixel loss. It has the characteristics of simple method, clear image, low cost, and prolonged use and maintenance time.

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  • Industrial monitoring video image sharpening method based on GAN network
  • Industrial monitoring video image sharpening method based on GAN network
  • Industrial monitoring video image sharpening method based on GAN network

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Embodiment

[0050] Such as figure 1 As shown, a GAN network-based industrial surveillance video image clearing method, the process is as follows:

[0051] 1) Collect video images, select 50,000 pictures as the training data set of the model, and the training images are low-resolution images input to the network and composite images stitched together as high-definition images for supervised learning.

[0052] 2) Input the training samples into the GAN network for training. The network includes a generation module and a discrimination module. The generation module generates a pseudo high-definition image according to the input low-resolution image, and the discriminator identifies the authenticity of the image. The specific process is as follows:

[0053] Step 1: collect original industrial video images, and collect at least two sets of video data as a training set. One group is the low-resolution video images that are blurred in the monitoring video caused by dust, smoke, and lighting ch...

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Abstract

The invention discloses an industrial monitoring video image sharpening method based on a GAN network. The industrial monitoring video image sharpening method comprises the following steps: step 1, acquiring an original industrial video image; 2, preprocessing the image data; 3, detecting whether a trained model is contained or not; 4, building a GAN network; 5, perfomring model training; 6, performing model testing to obtain a corresponding high-definition image; 7, checking the test effect, and if the model can generate a high-definition image according to the test image, determining that the model training is better and can meet the actual application requirements; if the test effect is not good, restarting the step 1 to add training samples, and performing training again; the method has the advantages of simple training process, small model, good effect and high calculation efficiency, and is very suitable for recovery and sharpness processing of the monitoring image in a complex industrial environment.

Description

technical field [0001] The present invention relates to the field of computer vision methods, in particular to a method for clearing industrial monitoring video images based on a GAN network. Background technique [0002] With the rapid and steady development of my country's industry, enterprises' intelligent monitoring in the production process is a very important part to ensure the safety of personnel, product quality and efficiency. However, in the actual industrial environment, due to dust, smog, and light changes, the monitoring video is blurred, insufficient light, and pixel loss lead to unclear pictures, which affect the monitoring effect. Frequent lens cleaning is required, resulting in a large maintenance workload. [0003] Image sharpening or image super-resolution reconstruction is an important processing method in the field of computer vision. It can restore the high-definition image according to the input low-definition image, and it is of great significance t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06T5/003G06N3/08G06T2207/10016G06T2207/20081G06N3/045
Inventor 杨延西毛如玉高异
Owner XIAN UNIV OF TECH
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