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:
Dec. 10, 2024

Filed:

Dec. 13, 2022
Applicant:

Tencent America Llc, Palo Alto, CA (US);

Inventors:

Ding Ding, Palo Alto, CA (US);

Xiaozhong Xu, State College, PA (US);

Shan Liu, San Jose, CA (US);

Assignee:

TENCENT AMERICA LLC, Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/86 (2014.01); G06N 3/08 (2023.01); H04N 19/136 (2014.01); H04N 19/167 (2014.01); H04N 19/176 (2014.01); H04N 19/42 (2014.01); H04N 19/80 (2014.01);
U.S. Cl.
CPC ...
H04N 19/86 (2014.11); G06N 3/08 (2013.01); H04N 19/136 (2014.11); H04N 19/167 (2014.11); H04N 19/176 (2014.11); H04N 19/42 (2014.11); H04N 19/80 (2014.11);
Abstract

A method and apparatus for reducing artifacts in a compressed image using a neural-network based deblocking filter. The method may include receiving at least one reconstructed image, wherein each reconstructed image comprises one or more reconstructed blocks and extracting boundary areas associated with boundaries of the one or more reconstructed blocks in the at least one reconstructed image. The extracted boundary areas may be input in a trained deblocking model to generate boundary areas having reduced artifacts and the trained deblocking mode is trained on training data based on estimated compression by a neural image compression (NIC) network. The edge areas associated with the generated boundary areas may be removed; and at least one reconstructed image with reduced artifacts may be generated based on the generated boundary areas.


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