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:
Sep. 03, 2019

Filed:

Mar. 30, 2015
Applicant:

Netflix, Inc, Los Gatos, CA (US);

Inventors:

Anne Aaron, Menlo Park, CA (US);

David Ronca, Campbell, CA (US);

Ioannis Katsavounidis, Los Angeles, CA (US);

Andy Schuler, San Jose, CA (US);

Assignee:

NETFLIX, INC., Los Gatos, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04N 19/146 (2014.01); H04N 19/124 (2014.01); H04N 19/154 (2014.01); H04N 21/234 (2011.01); H04N 21/2343 (2011.01);
U.S. Cl.
CPC ...
H04N 19/146 (2014.11); H04N 19/124 (2014.11); H04N 19/154 (2014.11); H04N 21/23418 (2013.01); H04N 21/23439 (2013.01);
Abstract

In one embodiment of the present invention, an encoding bitrate ladder selector tailors bitrate ladders to the complexity of source data. Upon receiving source data, a complexity analyzer configures an encoder to repeatedly encode the source data-setting a constant quantization parameter to a different value for each encode. The complexity analyzer processes the encoding results to determine an equation that relates a visual quality metric to an encoding bitrate. The bucketing unit solves this equation to estimate a bucketing bitrate at a predetermined value of the visual quality metric. Based on the bucketing bitrate, the bucketing unit assigns the source data to a complexity bucket having an associated, predetermined bitrate ladder. Advantageously, sagaciously selecting the bitrate ladder enables encoding that optimally reflects tradeoffs between quality and resources (e.g., storage and bandwidth) across a variety of source data types instead of a single, 'typical' source data type.


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