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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 12651317 B1

PDFFull Text
Date of Patent:
Jun. 09, 2026

Filed:

Mar. 15, 2024

Image processing method and device for removing perceptible noise from image

Applicant:

Samsung Electronics Co., Ltd., Suwon-si, KR;

Inventors:

Moonhee Kim, Suwon-si, KR;

Bongjoe Kim, Suwon-si, KR;

Sanghun Kim, Suwon-si, KR;

Assignee:

SAMSUNG ELECTRONICS CO., LTD., Suwon-si, KR;

Attorney:

Sughrue Mion, PLLC

Primary Examiner:

Eric Rush

Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 18/15 (2023.01); G06T 5/50 (2006.01); G06T 5/60 (2024.01); G06T 5/70 (2024.01); G06T 7/00 (2017.01); G06T 7/13 (2017.01); G06V 10/30 (2022.01); G06V 10/44 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06T 5/70 (2024.01); G06F 18/15 (2023.01); G06T 5/50 (2013.01); G06T 5/60 (2024.01); G06T 7/0002 (2013.01); G06T 7/13 (2017.01); G06V 10/30 (2022.01); G06V 10/44 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01); G06T 2207/20012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20172 (2013.01); G06T 2207/20192 (2013.01); G06T 2207/20212 (2013.01); G06T 2207/30168 (2013.01);
Abstract

The present disclosure relates to an image processing method and device for removing perceptible noise from an image. The disclosed image processing method includes: obtaining a noise-removed image from an image; obtaining removed noise from a difference between the image and the noise-removed image; obtaining a statistical feature of the noise-removed image and a statistical feature of the noise; determining a noise feature regarding whether noise of a pixel is perceptible noise or a perceptible detail, based on the statistical feature of the noise-removed image and the statistical feature of the noise; and performing a process of removing the perceptible noise from the image based on the noise feature of the pixel.

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