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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12175632 B1

PDFFull Text
Date of Patent:
Dec. 24, 2024

Filed:

Sep. 30, 2020

Image processing method and apparatus, device, and video processing method

Applicant:

Boe Technology Group Co., Ltd., Beijing, CN;

Inventors:

Yan Gao, Beijing, CN;

Guannan Chen, Beijing, CN;

Lijie Zhang, Beijing, CN;

Wenbin Chen, Beijing, CN;

Assignee:

BOE TECHNOLOGY GROUP CO., LTD., Beijing, CN;

Attorneys:

Raj S. Dave

Dave Law Group LLC

Primary Examiner:

Jon Chang

Int. Cl.
CPC ...
G06T 5/50 (2006.01); G06T 3/4046 (2024.01); G06T 3/4053 (2024.01); G06V 10/40 (2022.01); G06V 10/44 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); H04N 7/015 (2006.01); H04N 19/42 (2014.01);
U.S. Cl.
CPC ...
G06T 5/50 (2013.01); G06T 3/4046 (2013.01); G06T 3/4053 (2013.01); G06V 10/40 (2022.01); G06V 10/7747 (2022.01); G06V 10/776 (2022.01); G06V 10/803 (2022.01); G06V 10/82 (2022.01); H04N 7/015 (2013.01); H04N 19/42 (2014.11); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30168 (2013.01); G06V 10/454 (2022.01);
Abstract

An image processing method and apparatus, a device, a video processing method and a storage medium are provided. The image processing method includes: receiving an input image; and processing the input image by using the convolutional neural network to obtain an output image. A definition of the output image is higher than a definition of the input image. Processing the input image by using the convolutional neural network to obtain the output image includes: performing feature extraction on the input image; concatenating the input image and the plurality of first images; performing the feature extraction on the first image group; fusing the plurality of second images and the plurality of first images; concatenating the input image and the plurality of third images to obtain a second image group; and performing the feature extraction on the second image group to obtain the output image.

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