Image Defect Map Creation Using Batches of Digital Images

• US 20100321537A1
• Filed: 02/22/2010
• Published: 12/23/2010
• Est. Priority Date: 09/30/2003
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: FotoNation Ireland Limited (Adeia Inc.)
• Inventors: Corcoran, Peter, Zamfir, Marta, Steinberg, Eran, Prilutsky, Yury, Zamfir, Adrian, Bigioi, Petronel
• Granted Patent: US 8,369,650 B2
• Time in Patent Office: Days
• US Class Current: 348/241
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 5/77 Retouching; Inpainting; Scratch removal
• 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
• CPC Class Codes: H04N 25/68 applied to defects

Abstract

A method of automatically determining a need to service a digital image acquisition system including a digital camera with a lens assembly includes analyzing pixels within one or more acquired digital images according to probability determinations that such pixels correspond to blemish artifacts. It is automatically determined whether a threshold distribution of blemish artifacts is present within one or more of the digital images. A need for service is indicated when at least the threshold distribution is determined to be present.

Claims

1. A method of correcting defects in digital images, comprising:

using a processor;

acquiring a set of images with a device including a lens and image sensor;

computing a gray-scale version of a current image of the set of images;

computing a local mean of the current image computing a difference image based on differences between the gray-scale version and local mean version of the current image;

computing a current binary map that results after thresholding the difference image;

growing a gray map by adding to the current binary map with subsequent binary maps of subsequent images of the set;

generating a final binary map; and

correcting a defect within a digital image based on the final binary map.

2. The method of claim 1, comprising facilitating implementation of a binarization with an adaptive threshold.

3. The method of claim 1, further comprising thresholding to obtain a binary map.

4. The method of claim 3, wherein the threshold comprises an adaptive threshold that depends on number of processed images.

5. The method of claim 4, wherein the threshold is based on a percentage of the number of images.

6. The method of claim 3, further comprising calculating a label image.

7. The method of claim 6, further comprising eliminating defect regions that have an area greater than a defect size threshold.

8. The method of claim 7, wherein the defect size threshold comprises 800 pixels.

9. The method of claim 1, wherein the computing a local mean comprises computing low-pass filtering.

10. One or more processor-readable media having embedded therein code for programming a processor to perform a method of correcting defects in digital images, wherein the method comprising:

programming the processor;

acquiring a set of images with a device including a lens and image sensor;

computing a gray-scale version of a current image of the set of images;

computing a local mean of the current image

computing a difference image based on differences between the gray-scale version and local mean version of the current image;

computing a current binary map that results after thresholding the difference image; and

growing a gray map by adding to the current binary map with subsequent binary maps of subsequent images of the set.

11. The one or more processor-readable media of claim 10, the method comprising facilitating implementation of a binarization with an adaptive threshold.

12. The one or more processor-readable media of claim 10, wherein the method further comprises thresholding to obtain a binary map.

13. The one or more processor-readable media of claim 12, wherein the threshold comprises an adaptive threshold that depends on number of processed images.

14. The one or more processor-readable media of claim 13, wherein the threshold is based on a percentage of the number of images.

15. The one or more processor-readable media of claim 12, wherein the method further comprises calculating a label image.

16. The one or more processor-readable media of claim 15, wherein the method further comprises eliminating defect regions that have an area greater than a defect size threshold.

17. The one or more processor-readable media of claim 16, wherein the defect size threshold comprises 800 pixels.

18. The one or more processor-readable media of claim 10, wherein the computing a local mean comprises computing low-pass filtering.

19. An image acquisition and processing device that acquires and corrects defects in digital images, comprising a lens, an image sensor, a processor and a memory having code embedded therein for programming the processor to perform within the device the following method:

acquiring a set of images with a device including a lens and image sensor;

computing a gray-scale version of a current image of the set of images;

computing a local mean of the current image computing a difference image based on differences between the gray-scale version and local mean version of the current image;

computing a current binary map that results after thresholding the difference image; and

growing a gray map by adding to the current binary map with subsequent binary maps of subsequent images of the set.

20. The device of claim 19, the method comprising facilitating implementation of a binarization with an adaptive threshold.

21. The device of claim 19, wherein the method further comprises thresholding to obtain a binary map.

22. The device of claim 21, wherein the threshold comprises an adaptive threshold that depends on number of processed images.

23. The device of claim 22, wherein the threshold is based on a percentage of the number of images.

24. The device of claim 21, wherein the method further comprises calculating a label image.

25. The device of claim 24, wherein the method further comprises eliminating defect regions that have an area greater than a defect size threshold.

26. The device of claim 25, wherein the defect size threshold comprises 800 pixels.

27. The device of claim 19, wherein the computing a local mean comprises computing low-pass filtering.