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An image deblurring method and system based on depth learning

A deep learning and deblurring technology, applied in the field of image processing, can solve problems such as non-universal adaptation

Inactive Publication Date: 2018-12-25
北京飞搜科技有限公司
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Problems solved by technology

[0006] In order to overcome the problem that the existing deblurring technology needs to know the exact blur kernel in advance, resulting in no universal adaptation, the present invention provides an image deblurring method and system based on deep learning

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  • An image deblurring method and system based on depth learning
  • An image deblurring method and system based on depth learning
  • An image deblurring method and system based on depth learning

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Embodiment Construction

[0043] The specific embodiments of the present invention will be described in further detail below in conjunction with the drawings and embodiments. The following examples are used to illustrate the present invention, but not to limit the scope of the present invention.

[0044] figure 1 It is a schematic diagram of the overall process of a deep learning-based image deblurring method according to an embodiment of the present invention, such as figure 1 As shown, the present invention provides an image deblurring method based on deep learning, including:

[0045] S1, acquiring a target image to be deblurred, and preprocessing the target image;

[0046] Specifically, first obtain the blurred image to be deblurred and use it as the target image. The target image is then preprocessed, and the size of the target image is adjusted to a preset size, so that the size of the target image can adapt to the requirements of the input image of the preset neural network. In addition, other prepro...

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Abstract

The invention provides an image deblurring method and system based on depth learning, which obtains the target image to be deblurred and preprocesses the target image. The preprocessed target image isinputted to the preset neural network, and the corresponding deblurred image is obtained according to the output result of the preset neural network. Among them, the preset neural network is obtainedafter training according to fuzzy image samples and clear image samples. The method and the system can automatically deblur the blurred image by using a preset neural network to obtain the deblurredimage corresponding to the blurred image, and the method and the system do not need to know the exact blurring kernel in advance, and can be applied to any type of blurred image, and have wide generaladaptability. At the same time, the efficiency and accuracy of image processing, recognition and application can be effectively improved by deblurring the image before image processing, recognition and application.

Description

Technical field [0001] The present invention relates to the technical field of image processing, and more specifically, to an image deblurring method and system based on deep learning. Background technique [0002] Due to the influence of the environment and imaging equipment (such as the hardware conditions of the camera), the image quality will be more or less lost during the imaging process. Image blur is a common image degradation phenomenon. [0003] Generally, the types of image blur can be divided into the following types: defocus blur, Gaussian blur, motion blur, mixed blur and arbitrary blur. Among them, defocus blur refers to the unclear image caused by the lens not focusing properly or due to the large depth of field causing part of the scene to be out of focus; Gaussian blur refers to the unclear image caused by the influence of atmospheric turbulence on the scattering of object light. Clear; motion blur refers to the unclear image caused by the mixture of moving objec...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04
CPCG06T2207/20081G06T2207/10004G06N3/045G06T5/73
Inventor 刘一胶董远白洪亮熊风烨
Owner 北京飞搜科技有限公司
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