Image restoration method based on enhanced neural network, storage medium and system

A neural network and storage medium technology, applied in the field of neural network image restoration method, storage medium and system, can solve the problems of network degradation and slow convergence speed, and achieve the effect of improving performance and enhancing performance

Active Publication Date: 2018-12-25
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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Problems solved by technology

However, although the above methods have achieved certain effects on the image restoration problem, as the network gets deeper, the network degradation phenomenon becomes more and more serious, and the convergence speed is slow during the network training process.

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  • Image restoration method based on enhanced neural network, storage medium and system
  • Image restoration method based on enhanced neural network, storage medium and system
  • Image restoration method based on enhanced neural network, storage medium and system

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Embodiment Construction

[0051] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0052] The first embodiment of the present invention provides an image restoration method based on an enhanced neural network, such as figure 1 As shown, the method includes the following steps:

[0053] S1. Transform the image to be restored into a plurality of low-resolution images under different scaling factors, for example, reduce the image to be restored to 1 / 2, 1 / 3, 1 / 4 of the original image, etc.;

[0054] S2. Input multiple low-resolution images to the pre-trained first deep convolutional neural network respectively, so as to obtain multiple high-resolution images corresponding to different scaling factors;

[0055] S3. Transform the multiple high-resolution images in S2 into images of the same size as the image to be restored, and fuse these images to obtain a restored image.

[0056] Wherein, ...

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Abstract

The invention discloses an image restoration method based on an enhanced neural network. The method comprises the following steps: S1, converting an image to be restored into a plurality of low-resolution images under different zoom factors; S2, converting the image to be restored into a plurality of low-resolution images under different zoom factors; S3, converting the image to be restored into aplurality of low-resolution images. S2, respectively inputting a plurality of low-resolution images to a first depth convolution neural network trained in advance, thereby obtaining a plurality of high-resolution images under corresponding different scaling factors; S3, converting a plurality of high-resolution images in S2 into images having the same size as the image to be restored, and fusingthese images to obtain the restored images. The invention also discloses a corresponding storage medium and an image restoration system. The invention can prevent the network from being degraded in the training process and accelerate the convergence speed.

Description

technical field [0001] The invention relates to the field of image restoration, in particular to an image restoration method, storage medium and system based on an enhanced neural network. Background technique [0002] With the development of network technology and communication technology, image processing is applied in more and more fields, such as: aviation exploration, weather prediction, disaster rescue and video entertainment, etc. However, the shooting equipment will be affected when taking pictures in smog, rain, snow, dark light and equipment shaking. This kind of problem of obtaining the original image through restoration is called the image restoration problem. The image restoration problem is a classic computer vision and model recognition problem. Among them, image super-resolution and image denoising are typical and important image restoration problems, which aim to restore high-resolution images from low-resolution images, which have been applied to medical ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06T5/00G06N3/04G06N3/08
CPCG06N3/08G06T5/009G06T5/50G06T2207/20221G06N3/045
Inventor 田春伟徐勇
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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