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:
Nov. 28, 2023

Filed:

Jun. 21, 2021
Applicant:

Ping an Technology (Shenzhen) Co., Ltd., Shenzhen, CN;

Inventors:

Yuchuan Gou, Sunnyvale, CA (US);

Juihsin Lai, Santa Clara, CA (US);

Mei Han, Palo Alto, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/50 (2022.01); G06T 3/40 (2006.01); G06V 20/10 (2022.01); G06F 18/214 (2023.01); G06F 18/25 (2023.01);
U.S. Cl.
CPC ...
G06T 3/4076 (2013.01); G06F 18/214 (2023.01); G06F 18/253 (2023.01); G06T 3/4046 (2013.01); G06V 10/50 (2022.01); G06V 20/188 (2022.01);
Abstract

A system and a method for super-resolution image processing in remote sensing are disclosed. One or more sets of multi-temporal images with an input resolution and one or more first target images with a first output resolution are generated from one or more data sources. The first output resolution is higher than the input resolution. Each set of multi-temporal images is processed to improve an image match in the corresponding set of multi-temporal images. The one or more sets of multi-temporal images are associated with the one or more first target images to generate a training dataset. A deep learning model is trained using the training dataset. The deep learning model is provided for subsequent super-resolution image processing.


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