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Network model training method, image processing method and related equipment

A technology for training images and network models, applied in the field of image processing, can solve problems such as poor noise reduction ability and image ghosting

Active Publication Date: 2021-12-28
HONOR DEVICE CO LTD
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, the above scheme has poor noise reduction ability, and the processed image has problems such as ghosting (antific)

Method used

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  • Network model training method, image processing method and related equipment
  • Network model training method, image processing method and related equipment
  • Network model training method, image processing method and related equipment

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Embodiment Construction

[0045] The technical solution in this application will be described below with reference to the accompanying drawings.

[0046] In the description of the embodiments of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association of associated objects A relationship means that there may be three kinds of relationships, for example, A and / or B means: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "plurality" refers to two or more than two.

[0047] Hereinafter, the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, a feature defined as "first" and "second" may explicitly or implicitly include one or more of these features....

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Abstract

The invention provides a network model training method, an image processing method and related equipment, and relates to the technical field of images. The network model training method comprises the steps: obtaining a first training image pair; training an initial generator by using the first training image pair to obtain an intermediate generator; obtaining a second training image pair; and training an initial network model by using the first training image pair and the second training image pair to obtain a first target network model. A deep learning method is utilized, demosaicing, noise reduction and super-resolution are carried out in a combined mode, and in the process of converting the image of an RAW domain into the image of an RGB domain, the purposes of reducing noise, reducing ghosting and improving the definition of the image are achieved.

Description

technical field [0001] The present application relates to the field of image processing, in particular to a network model training method, an image processing method and related equipment. Background technique [0002] With the widespread use of electronic devices, using electronic devices to take pictures has become a daily behavior in people's lives. Taking the mobile phone as an example of an electronic device, various technologies for improving image quality have emerged, such as demosaic, denoise, super-resolution (SR) and so on. [0003] In the prior art, for an original image acquired by a mobile phone, that is, an image in the RAW domain, noise reduction and super-resolution are usually performed first, and then demosaicing is performed. However, the above solution has problems such as poor noise reduction capability and antific image after processing. Therefore, a new image processing method is urgently needed to effectively improve the quality of acquired images....

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06T5/00G06T3/40
CPCG06N3/08G06T3/4053G06T2207/10024G06T2207/20081G06N3/045G06T5/80G06T5/73G06T5/70
Inventor 曹瑞
Owner HONOR DEVICE CO LTD
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