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, 2019

Filed:

Jun. 22, 2017
Applicant:

Disney Enterprises, Inc., Burbank, CA (US);

Inventors:

Christopher Schroers, SaarbrĂĽcken, DE;

Henning Zimmer, Zurich, CH;

Alexander Sorkine Hornung, Zurich, CH;

Assignee:

Disney Enterprises, Inc., Burbank, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/00 (2006.01); H04N 5/213 (2006.01); G06T 5/20 (2006.01); G06T 1/20 (2006.01); H04N 5/21 (2006.01);
U.S. Cl.
CPC ...
G06T 5/002 (2013.01); G06T 1/20 (2013.01); G06T 5/003 (2013.01); G06T 5/20 (2013.01); H04N 5/21 (2013.01); H04N 5/213 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20172 (2013.01); G06T 2207/20182 (2013.01);
Abstract

According to one implementation, a video processing system includes a computing platform having a hardware processor and a system memory storing a sample-based video denoising software code. The hardware processor executes the sample-based video denoising software code to receive a video sequence, and select a reference frame of the video sequence to denoise. For each pixel of the reference frame, the hardware processor executes the sample-based video denoising software code to map the pixel to a sample pixel in each of other frames of the video sequence, identify a first confidence value corresponding to each of the sample pixels based on the mapping, identify a second confidence value corresponding to each of the sample pixels based on the frame that includes the sample pixel, and denoise the pixel based on a weighted combination of the sample pixels determined using the first confidence values and the second confidence values.


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