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:
Feb. 25, 2020

Filed:

Oct. 18, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Conrad M. Albrecht, White Plains, NY (US);

Hendrik F. Hamann, Bedford, NY (US);

Siyuan Lu, Yorktown Heights, NY (US);

Sharathchandra U. Pankanti, Darien, CT (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/32 (2006.01); G06T 3/40 (2006.01); G06T 5/00 (2006.01); G06T 7/55 (2017.01); G06T 7/45 (2017.01);
U.S. Cl.
CPC ...
G06T 3/4053 (2013.01); G06T 5/003 (2013.01); G06T 7/45 (2017.01); G06T 7/55 (2017.01); G06T 2207/10032 (2013.01); G06T 2207/20016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30208 (2013.01);
Abstract

A system and method to enhance observation resolution using continuous learning include obtaining a first image of a surface area from a first satellite, and obtaining a second image of the surface area from a second satellite. The first image has a lower spatial resolution than the second image, and temporal resolution of the first images obtained by the first satellite is higher than temporal resolution of the second images obtained by the second satellite. The method also includes determining a convolution matrix A or training a neural network, obtaining additional one or more of the first images prior to obtaining an additional one of the second images, and generating a new image from each of the one or more of the first images using the convolution matrix A or the neural network. The new image has a higher spatial resolution than the one or more of the first images.


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