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:
Jun. 03, 2014

Filed:

Mar. 16, 2013
Applicant:

Cognex Corporation, Natick, MA (US);

Inventors:

E. John McGarry, La Jolla, CA (US);

William M. Silver, Nobleboro, ME (US);

Assignee:

Cognex Corporation, Natick, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04N 5/228 (2006.01); H04N 9/64 (2006.01); H04N 5/225 (2006.01); H04N 3/14 (2006.01); G06K 9/64 (2006.01); G06K 9/40 (2006.01);
U.S. Cl.
CPC ...
Abstract

A system and method captures a moving image of a scene that can be more readily de-blurred as compared to images captured through other methods operating on equivalent exposure-time intervals. Rather than stopping and starting the light measurement during the exposure-time interval, photo-generated current is switched between multiple charge storage sites in accordance with a temporal switching pattern that optimizes the conditioning of the solution to the inverse blur transform. By switching the image intensity signal between storage sites all of the light energy available during the exposure-time interval is transduced to electronic charge and captured to form a temporally decomposed representation of the moving image. As compared to related methods that discard approximately half of the image intensity signal available over an equivalent exposure-time interval, such a temporally decomposed image is a far more complete representation of the moving image and more effectively de-blurred using simple linear de-convolution techniques.


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