Digital camera with built-in lens calibration table

• US 20050068452A1
• Filed: 05/10/2004
• Published: 03/31/2005
• 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
• Granted Patent: US 7,590,305 B2
• Time in Patent Office: Days
• US Class Current: 348/335
• CPC Class Codes: H04N 1/4097 Removing errors due external factors, e.g. dust, scratches
• CPC Class Codes: H04N 23/663 for controlling interchangeable camera parts based on electronic image sensor signals
• CPC Class Codes: H04N 23/81 for suppressing or minimising disturbance in the image signal generation
• 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

Abstract

A digital camera that automatically corrects dust artifact regions within acquired images by compiling a dust map includes an optical system for acquiring an image with a corresponding dust calibration table for such optical system, including a lens assembly and an aperture stop, in which the corresponding dust calibration map can reside. A transformation between the dust map and the specific lens calibration table, enables the use for a single dust map in multiple instances of lenses and focal length, without the need to recalibrate the digital camera for each instance.

Claims

1. A digital camera that automatically corrects dust artifact regions within acquired images, comprising:

(a) an optical system for acquiring an image including a lens assembly and an aperture stop;

(b) an electronic sensor array for collecting image data with multiple pixels that collectively correspond to the acquired image;

(c) a lens calibration table corresponding to said optical system that includes information describing dust location and appearance as a function of optical parameters;

(d) a master dust map describing a physical manifestation of dust artifacts on said sensor array;

(e) a manifestation of the master dust map for a specific lens and focal length, calculated as a transformation of the master dust map based on the lens calibration table; and

(f) digital processing electronics including a processor for converting processing the digital data according to programming instructions; and

(g) wherein said dust artifacts are corrected for said acquired image based on the manifestation of the master dust map.

2. The camera of claim 1, wherein said lens calibration table is located inside the lens.

3. The camera of claim 1, wherein said lens calibration table is located in an external application.

4. The camera of claim 1, wherein said lens calibration table is downloadable from a server

5. The camera of claim 1, wherein said master dust map is a statistical dust map.

6. The camera of claim 5, wherein additional images are digitally-acquired with said digital camera, and said statistical dust map is dynamically updated.

7. The camera of claim 6, wherein said statistical map comprises probabilities based on comparisons with suspected equivalent dust artifact regions within said additional images.

8. The camera of claim 7, wherein determining of said probabilities is based on a pixel analysis of the suspected dust artifact regions in view of predetermined characteristics indicative of the presence of a dust artifact region.

9. The camera of claim 5, wherein whether said additional digitally-acquired images have non-contradicting data that said probability that certain pixels correspond to dust artifact regions within said images is validated prior to correcting pixels corresponding to correlated dust artifact regions within said images based on the manifestation of said master statistical dust map.

10. The camera of claim 1, wherein said dust artifacts are corrected on a image from raw format.

11. The camera of claim 1, wherein said dust artifacts are corrected on a processed image after being converted from raw format to a known red, green, blue representation.

12. The camera of claim 1, wherein said dust artifacts are corrected by replacing said pixels within said one or more digitally-acquired images with new pixels.

13. The camera of claim 1, wherein said dust artifacts are corrected by enhancing values of pixels within said one or more digitally-acquired images.

14. A method performed within a digital image acquisition device that is coupled with a lens assembly including optical and signal coupling, the method for automatically correcting dust artifact within images acquired by the device, comprising:

(a) acquiring one or more initial digital images within said digital acquisition device;

(b) determining that certain pixels correspond to dust artifact regions within said images;

(c) receiving through said signal coupling one or more values of one or more extracted parameters relating to the optical system that are embedded within the lens assembly; and

(d) correcting pixels corresponding to correlated dust artifact regions within further digitally-acquired images based on the determining and the one or more extracted parameter values.

15. The method of claim 14, wherein said receiving further comprises receiving data based on a lens calibration table corresponding to said lens assembly that includes information describing the dust location and appearance as a function of the extracted parameters relating to the optical system.

16. The method of claim 14, wherein the one or more extracted parameters comprise magnification, lens type, or focal length, or combinations thereof.

17. The method of claim 14, wherein the correcting comprises:

(i) associating dust artifact regions with one or more values of one or more extracted parameters relating to the optical system of the digital acquisition device when the images were acquired; and

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

(iii) wherein the correcting is based on the statistical dust map.

18. The method of claim 17, wherein the correcting further comprises:

(i) loading the statistical dust map;

(ii) loading extracted parameter information of a present image;

(iii) performing calculations within the statistical dust map having extracted parameter variable-dependencies; and

(iv) comparing dust artifact detection data with the extracted parameter dependent statistical dust map data.

19. A method performed within a digital image acquisition device that is coupled with a lens assembly including optical and signal coupling, the method for automatically correcting imaging artifacts within images acquired by the device, comprising:

(a) acquiring one or more initial digital images within said digital acquisition device;

(b) determining that certain pixels correspond to artifact regions within said images;

(c) receiving through said signal coupling data based on a lens calibration table corresponding to said lens assembly that includes information describing artifact location and appearance as a function of one or more values of one or more extracted parameters relating to the optical system that are embedded within the lens assembly; and

(d) correcting pixels corresponding to correlated artifact regions within further digitally-acquired images based on the determining and the one or more extracted parameter values.

20. The method of claim 19, wherein the one or more extracted parameters comprise magnification, lens type, or focal length, or combinations thereof.

21. The method of claim 19, wherein the correcting comprises:

(i) associating artifact regions with one or more values of one or more extracted parameters relating to the optical system of the digital acquisition device when the images were acquired; and

(ii) forming a statistical map including mapped artifact regions based on the artifact determining and associating,

(iii) wherein the correcting is based on the statistical map.

22. The method of claim 21, wherein the correcting further comprises:

(i) loading the statistical map;

(ii) loading extracted parameter information of a present image;

(iii) performing calculations within the statistical map having extracted parameter variable-dependencies; and

(iv) comparing artifact detection data with the extracted parameter dependent statistical map data.