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. 10, 2019

Filed:

Nov. 11, 2016
Applicant:

University of Virginia Patent Foundation, Charlottesville, VA (US);

Inventors:

Haoyi Liang, Charlottesville, VA (US);

Daniel Stuart Weller, Charlottesville, VA (US);

Assignee:

UNIVERSITY OF VIRGINIA PATENT FOUNDATION, Charlottesville, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 5/00 (2006.01); G06T 5/50 (2006.01); H04L 29/08 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0002 (2013.01); G06T 5/001 (2013.01); G06T 5/50 (2013.01); G06T 2207/20056 (2013.01); G06T 2207/30168 (2013.01); H04L 67/10 (2013.01);
Abstract

An image quality assessment and restoration system may include a processor and a memory storing instructions to receive an input image, receive a predetermined number of parameter candidates, generate a reconstructed image from the input image for each parameter candidate, sort the reconstructed images by the overall comparative quality between them and determine the best reconstructed image, calculate the overall comparative qualities between the remaining reconstructed images and the best reconstructed image, eliminate any parameter candidates that are suboptimal based on the calculated overall comparative quality, iteratively generate and sort additional reconstructed images and eliminate suboptimal parameter candidates until each of the remaining parameter candidates is converged, and output the converged parameters for use in image restoration. The overall comparative quality may depend upon the local gradient-based structure information and/or the global texture quality information.


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