US 12,482,065 B2
Learning based bad pixel correction
Igal Avishai, Tel-Aviv (IL); Gal Bitan, Tel-Aviv (IL); and Roy Yam, Tel-Aviv (IL)
Assigned to SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed by SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed on Mar. 30, 2022, as Appl. No. 17/657,171.
Prior Publication US 2023/0316471 A1, Oct. 5, 2023
Int. Cl. G06T 5/20 (2006.01); G06T 9/00 (2006.01); G06V 10/22 (2022.01); G06V 10/762 (2022.01); G06V 10/774 (2022.01); G06V 10/778 (2022.01); H04N 23/80 (2023.01)
CPC G06T 5/20 (2013.01) [G06T 9/00 (2013.01); G06V 10/22 (2022.01); G06V 10/762 (2022.01); G06V 10/7747 (2022.01); G06V 10/778 (2022.01); H04N 23/80 (2023.01); G06T 2207/20081 (2013.01)] 13 Claims
OG exemplary drawing
 
1. A method for image processing, comprising:
receiving an image including a bad pixel;
identifying a patch of pixels surrounding the bad pixel;
generating a patch descriptor corresponding to the patch;
selecting a patch descriptor key corresponding to the patch descriptor from a dictionary including pairs of patch descriptor keys and filters;
comparing the patch descriptor to each of a plurality of patch descriptor keys in the dictionary;
obtaining a similarity value for each of the plurality of patch descriptor keys in the dictionary based on a result of the comparison, wherein the similarity value comprises a distance between the patch descriptor and a corresponding patch descriptor key;
identifying the selected patch descriptor key based on the similarity value;
identifying a filter paired with the identified patch descriptor key among the pairs of patch descriptor keys and filters in the dictionary; and
correcting the bad pixel by applying the identified filter to the patch.