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:
Jul. 24, 2018

Filed:

Jun. 05, 2015
Applicants:

Xun Xu, Cupertino, CA (US);

Peng YE, Foster City, CA (US);

Inventors:

Xun Xu, Cupertino, CA (US);

Peng Ye, Foster City, CA (US);

Assignee:

SONY CORPORATION, Tokyo, JP;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04N 19/176 (2014.01); H04N 19/103 (2014.01); H04N 19/117 (2014.01); H04N 19/154 (2014.01);
U.S. Cl.
CPC ...
H04N 19/176 (2014.11); H04N 19/103 (2014.11); H04N 19/117 (2014.11); H04N 19/154 (2014.11);
Abstract

A system and method for facilitating inhibiting banding in video data, in part by anticipating when banding may occur given certain encoder parameters. An example method includes receiving an input stream of video data; extracting feature information characterizing the stream of video data; using a feed-forward neural network to process the feature information to estimate when a particular block of the stream of video data will exhibit an artifact when encoded using certain Quantization Parameters (QPs); incorporating the indication into metadata associated with the stream of video data; and transferring the stream of video data and metadata to a video encoder. In a more specific embodiment, the feature information includes color information and texture information, and the neural network includes a feed-forward neural network that includes a classifier with a sigmoid activation function, and which has been trained using a cross-entropy cost function.


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