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. 26, 2019

Filed:

Jan. 19, 2017
Applicant:

Nuctech Company Limited, Haidian District, Beijing, CN;

Inventors:

Zhiqiang Chen, Beijing, CN;

Yuanjing Li, Beijing, CN;

Li Zhang, Beijing, CN;

Ziran Zhao, Beijing, CN;

Yaohong Liu, Beijing, CN;

Jianping Gu, Beijing, CN;

Zhiming Wang, Beijing, CN;

Assignee:

Nuctech Company Limited, Haidian District, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06T 5/00 (2006.01); G06T 7/00 (2017.01); G06T 3/00 (2006.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0002 (2013.01); G06K 9/6245 (2013.01); G06K 9/6298 (2013.01); G06T 5/002 (2013.01); G06K 2009/4695 (2013.01); G06T 3/0056 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20021 (2013.01);
Abstract

A method of evaluating an image quality for an imaging system and the imaging system are provided. The method in some examples includes: acquiring an image to be evaluated which is generated by the imaging system; extracting a number of sub-images from the image; obtaining a coefficient vector indicating a degree of sparsity by applying a sparse decomposition on the sub-images based on a pre-set redundant sparse representation dictionary; and performing a linear transformation on the coefficient vector so as to obtain an evaluation value for the image quality. The sparse dictionary is learned by only using a few high quality perspective images, and then the image quality is evaluated based on the sparse degree of the image obtained by using the sparse dictionary. A convenient and rapid no-reference image quality evaluation is achieved.


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