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:
Apr. 07, 2026

Filed:

Mar. 22, 2023
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Samira Pouyanfar, San Jose, CA (US);

Sunando Sengupta, Berkshire, GB;

Eric Chris Wolfgang Sommerlade, Oxford, GB;

Anjali S. Parikh, Redmond, WA (US);

Ebey Paulose Abraham, Oxford, GB;

Brian Timothy Hawkins, Sammamish, WA (US);

Mahmoud Mohammadi, Redmond, WA (US);

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/50 (2006.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06T 7/194 (2017.01); G06V 40/16 (2022.01);
U.S. Cl.
CPC ...
G06T 5/50 (2013.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06T 7/194 (2017.01); G06V 40/167 (2022.01); G06T 2207/20081 (2013.01);
Abstract

The present disclosure relates to an image restoration system that efficiently and accurately produces high-quality images captured under low-light and/or low-quality environmental conditions. To illustrate, when a user is in a low-lit environment and participating in a video stream, the image restoration system enhances the quality of the image by dynamically re-lighting the user's face. Moreover, it significantly enhances the image quality to the extent that other users viewing the video stream are unaware of the poor environmental conditions of the user. In addition, the image restoration system creates and utilizes an image restoration machine-learning model to improve the quality of low-quality images by re-lighting and restoring them in real time. Various implementations combine an autoencoder model with a distortion classifier model to create the image restoration machine-learning model.


Find Patent Forward Citations

Loading…