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.

Date of Patent:
May. 26, 2026

Filed:

Apr. 09, 2024
Applicant:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Inventors:

Chengwei Peng, Shenzhen, CN;

Yang Yi, Shenzhen, CN;

Yi Zhou, Shenzhen, CN;

Xiaoming Yu, Shenzhen, CN;

Yiting Xu, Shenzhen, CN;

Feng Li, Shenzhen, CN;

Xiaoxiang Zuo, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/70 (2024.01); G06T 3/40 (2006.01); G06T 5/20 (2006.01); G06T 7/11 (2017.01); G06T 7/246 (2017.01); G06T 7/90 (2017.01);
U.S. Cl.
CPC ...
G06T 5/70 (2024.01); G06T 3/40 (2013.01); G06T 5/20 (2013.01); G06T 7/11 (2017.01); G06T 7/248 (2017.01); G06T 7/90 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20021 (2013.01);
Abstract

An image noise reduction method including: obtaining a first image to be processed and a second image as a reference image; obtaining a block of the first image by dividing the first image; determining a motion intensity of the block based on the second image; obtaining filter coefficient description information matching the motion intensity based on: a first pixel difference of a first pixel point value of the first image and a second pixel point value of the second image, and a filter coefficient; obtaining a target pixel difference between a third pixel point value of the block and a fourth pixel point value of the second image; determining a target filter coefficient corresponding to the target pixel difference based on the filter coefficient description information; and determining a target noise reduction image of the first image based on the target filter coefficient.


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