AUTOFOCUS TECHNIQUE UTILIZING GRADIENT HISTOGRAM DISTRIBUTION CHARACTERISTICS

• US 20110109764A1
• Filed: 09/24/2008
• Published: 05/12/2011
• Est. Priority Date: 09/24/2008
• Status: Abandoned Application

• Current Assignee: Nikon Corporation
• Original Assignee: Nikon Corporation
• Inventors: Hong, Li
• Application Number:
  US13/001,768
• Publication Number:
  US 20110109764A1
• Time in Patent Office: Days
• US Class Current: 348/222.1
• CPC Class Codes: G02B 7/36 using image sharpness techniques , e.g. image processing techniques for generating autofocus signals image data processing per se G06T; in cameras having a solid state image sensor H04N23/67
• CPC Class Codes: H04N 23/53 of electronic viewfinders, e.g. rotatable or detachable
• CPC Class Codes: H04N 23/633 for displaying additional information relating to control or operation of the camera
• CPC Class Codes: H04N 23/67 Focus control based on electronic image sensor signals

Abstract

A method for estimating if an optical assembly (238) is focused on a scene (12) includes the steps of: capturing information for an image (14) of the scene (12); determining an image gradient histogram distribution (360) of at least a portion of the image (14); determining a Gaussian model gradient histogram distribution (361) of the image (14); and comparing at least a portion of the image gradient histogram distribution (360) to the Gaussian model gradient histogram distribution (361) of the image (14) to estimate if the image (14) is properly focused.

Claims

1. A method for estimating if an optical assembly is focused on a scene, the method comprising the steps of:

capturing information for an image of the scene;

determining an image gradient histogram distribution of at least a portion of the image;

determining a Gaussian model gradient histogram distribution of at least a portion of the image; and

comparing at least a portion of the image gradient histogram distribution to the Gaussian model gradient histogram distribution of the image to estimate if the image is in focus.

2. The method of claim 1 wherein the step of capturing information includes the step of capturing information for a plurality of alternative images from the scene, wherein the step of determining an image gradient histogram distribution includes the step of determining an image gradient histogram distribution for at least a portion of each of the plurality of alternative images, and wherein the step of comparing includes the step of comparing at least a portion of the image gradient histogram distribution for each of the alternative images to a Gaussian model gradient histogram distribution of each image to estimate which of the alternative images is in focus.

3. The method of claim 2 wherein the step of comparing includes the step of selecting the image having the greatest number of large gradients as being in focus.

4. The method of claim 1 wherein the step of comparing includes the step of comparing an image tail section of the image gradient histogram distribution with a Gaussian tail section of the Gaussian model gradient histogram distribution.

5. The method of claim 4 wherein the image is in focus if the image tail section is greater than the Gaussian tail section.

6. The method of claim 5 wherein the image is in not in focus if the image tail section is less than the Gaussian tail section.

7. A method for estimating when an optical assembly is focused on a scene, the method comprising the steps of:

capturing a plurality of images of the scene, each image being captured with the optical assembly at a different adjustment; and

determining an image gradient histogram distribution for each of images.

8. The method of claim 7 further comprising the step of comparing at least a portion of the image gradient histogram distribution for each of the images to each other to estimate which image is best focused.

9. The method of claim 7 wherein the step of comparing includes the step of selecting the image having the greatest number of large gradients as being in focus.

10. The method of claim 7 wherein the step of comparing includes the step of comparing an image tail section of each image gradient histogram distribution.

11. The method of claim 10 wherein the image which includes the largest tail section is selected as being in focus.

12. An image apparatus for capturing an image of a scene, the image apparatus comprising:

a capturing system for capturing information for a thru image of the scene;

a control system that (i) determines an image gradient histogram distribution of at least a portion of the thru image, (ii) determines a Gaussian model gradient histogram distribution of the thru image, and (iii) compares at least a portion of the image gradient histogram distribution to the Gaussian model gradient histogram distribution of the thru image to estimate if the thru image is in focus.

13. The image apparatus of claim 12 wherein the capturing system captures information for a plurality of alternative thru images from the scene with an optical assembly alternative adjustments, and wherein the control system (i) determines an image gradient histogram distribution for at least a portion of each of the plurality of alternative thru images, and (ii) compares at least a portion of the image gradient histogram distribution for each of the alternative images to the Gaussian model gradient histogram distribution to estimate which of the alternative thru images is in focus.

14. The image apparatus of claim 13 wherein the control system selects the thru image having the greatest number of large gradients as being in focus.

15. The image apparatus of claim 12 wherein the control system compares an image tail section of the image gradient histogram distribution with a Gaussian tail section of the Gaussian model gradient histogram distribution.

16. The image apparatus of claim 15 wherein the thru image is in focus if the image tail section is greater than the Gaussian tail section.

17. The image apparatus of claim 16 wherein the thru image is in not in focus if the image tail section is less than the Gaussian tail section.

18. An image apparatus for capturing an image of a scene, the image apparatus comprising:

an optical assembly;

a capturing system for capturing information for a plurality of thru images of the scene with each thru image being captured while the optical assembly is at a different adjustment; and

a control system that determines an image gradient histogram distribution for each of the thru image.

19. The image apparatus of claim 18 wherein the control system compares at least a portion of the image gradient histogram distribution for each of the images to each other to estimate which image is best focused.

20. The image apparatus of claim 18 wherein the control system selects the image having the greatest number of large gradients as being in focus.

21. The image apparatus of claim 18 wherein the control system compares an image tail section of each image gradient histogram distribution.

22. The image apparatus of claim 21 wherein the control system selects the thru image which includes the largest tail section is selected as being in focus.