Automated statistical self-calibrating detection and removal of blemishes in digital images based on multiple occurrences of dust in images

• US 20080144965A1
• Filed: 02/15/2008
• Published: 06/19/2008
• Est. Priority Date: 09/30/2003
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: FotoNation Vision Limited (Adeia Inc.)
• Inventors: Steinberg, Eran, Prilutsky, Yury, Zamfir, Adrian, Bigioi, Petronel, Corcoran, Peter, Buzuloiu, Vasile, Zamfir, Marta, Ursu, Danutz
• Granted Patent: US 7,536,060 B2
• Time in Patent Office: Days
• US Class Current: 382/275
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/155 Removing patterns interfering with the pattern to be recognised, such as ruled lines or underlines
• CPC Class Codes: H04N 23/811 by dust removal, e.g. from surfaces of the image sensor or processing of the image signal output by the electronic image sensor
• CPC Class Codes: H04N 25/67 applied to fixed-pattern noise, e.g. non-uniformity of response

Abstract

A method automatically corrects dust artifact within images acquired by a system including a digital acquisition device including a lens assembly. Multiple original digital images are acquired with the digital acquisition device. Probabilities that certain pixels correspond to dust artifact regions within the images are determined based at least in part on a comparison of suspected dust artifact regions within two or more of the images. Probable dust artifact regions are associated with extracted parameter values relating to the lens assembly when the images were acquired. A statistical dust map is formed including mapped dust regions based on the determining and associating. Pixels corresponding to correlated dust artifact regions are corrected within further digitally-acquired images based on the associated statistical dust map.

Claims

1. A method of automatically correcting dust artifact within images acquired by a system including a digital acquisition device including a lens assembly, comprising:

(a) acquiring multiple original digital images with said digital acquisition device;

(b) determining probabilities that certain pixels correspond to dust artifact regions within said images based at least in part on a comparison of suspected dust artifact regions within two or more of said images;

(c) associating probable dust artifact regions with one or more values of one or more extracted parameters relating to the lens assembly of the digital acquisition device when the images were acquired;

(d) forming a statistical dust map including mapped dust regions based on the dust artifact determining and associating; and

(e) correcting pixels corresponding to correlated dust artifact regions within further digitally-acquired images based on the associated statistical dust map.