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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.

Patent No.:

US 11854166 B1

PDFFull Text
Date of Patent:
Dec. 26, 2023

Filed:

Mar. 29, 2019

Apparatus and method using baseline estimation and half-quadratic minimization for the deblurring of signal data

Applicant:

Leica Microsystems Cms Gmbh, Mannheim, DE;

Inventors:

Kai Walter, Schriesheim, DE;

Florian Ziesche, Mannheim, DE;

Assignee:

LEICA MICROSYSTEMS CMS GMBH, Mannheim, DE;

Attorney:

Leydig, Voit & Mayer, Ltd.

Primary Examiner:

Jose L Couso

Int. Cl.
CPC ...
G06T 5/00 (2006.01); G06T 5/10 (2006.01); G06T 5/20 (2006.01); H04L 25/02 (2006.01); G06V 10/30 (2022.01); G06F 17/13 (2006.01); G06F 17/15 (2006.01); G06T 7/00 (2017.01); G02B 7/38 (2021.01); G02B 21/12 (2006.01); G02B 21/24 (2006.01); H04N 25/615 (2023.01);
U.S. Cl.
CPC ...
G06T 5/003 (2013.01); G02B 7/38 (2013.01); G02B 21/12 (2013.01); G02B 21/244 (2013.01); G06F 17/13 (2013.01); G06F 17/15 (2013.01); G06T 5/002 (2013.01); G06T 5/10 (2013.01); G06T 5/20 (2013.01); G06T 7/0012 (2013.01); G06V 10/30 (2022.01); H04L 25/025 (2013.01); H04N 25/615 (2023.01); G06T 2207/10056 (2013.01); G06T 2207/10068 (2013.01); G06T 2207/20056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01);
Abstract

A method for estimating baseline in a signal, the signal being represented by input signal data (I(x)), includes estimating a baseline contribution (I(x)) in the signal to obtain baseline estimation data (f(x)), wherein the baseline estimation data (f(x)) are computed as a fit to at least a subset of the input signal data (I(x)) by minimizing a least-square minimization criterion (M(f(x))). Deblurred output signal data (O(x)) are obtained based on the baseline estimation data (f(x)) and the input signal data (I(x)). The least-square minimization criterion (M(f(x))) comprises a penalty term (P(f(x))).

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