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:
May. 19, 2026

Filed:

Apr. 20, 2023
Applicant:

Nokia Technologies Oy, Espoo, FI;

Inventors:

Pekka Astola, Tampere, FI;

Jani Lainema, Tampere, FI;

Ramin Ghaznavi Youvalari, Tampere, FI;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/105 (2014.01); H04N 19/117 (2014.01); H04N 19/176 (2014.01); H04N 19/186 (2014.01);
U.S. Cl.
CPC ...
H04N 19/105 (2014.11); H04N 19/117 (2014.11); H04N 19/176 (2014.11); H04N 19/186 (2014.11);
Abstract

A method comprising: receiving an image block unit of a frame, the image block unit comprising samples in color channels comprising at least one chrominance channel and one luminance channel (); reconstructing samples of said luminance channels of the image block unit (); determining a reference area for predicting target samples of at least one color channel of the image block unit, wherein said reference area comprises one or more of reference samples in a neighboring block in current color channel/frame, in the neighboring of a co-located block in reference color channel/frame; and/or inside the co-located block in reference color channel/frame (); determining filter coefficients of a filter for said predicting based the reference samples and a shape of the filter (); reconstructing the target samples of at least one color channel of the image block unit using said prediction based on the samples of said reference area and the filter coefficients (); computing an autocorrelation matrix for the reconstructed target samples of the image block unit (); computing autocorrelation matrices for a plurality of neighboring image blocks units of said image block unit (); mixing the autocorrelation matrices of each of the plurality of neighboring image blocks units separately with the autocorrelation matrix of said image block unit (); and storing the mixed autocorrelation matrices for said image block unit ().


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