COMBINED FORWARD AND REVERSE CORRELATION

• US 20070189637A1
• Filed: 06/01/2006
• Published: 08/16/2007
• Est. Priority Date: 02/13/2006
• Status: Active Grant

• Current Assignee: Medit Corp.
• Original Assignee: 3M Innovative Properties Company (3M Company)
• Inventors: Rohaly, Janos
• Granted Patent: US 7,606,424 B2
• Time in Patent Office: Days
• US Class Current: 382/278
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 7/223 using block-matching
• CPC Class Codes: G06V 10/761 Proximity, similarity or dissimilarity measures

Abstract

Improved correlation techniques employ data from forward (template-to-reference) and reverse (reference-to-template) correlation to identify valid correlation peaks, enforce symmetry in correlation peaks, and/or combine forward and reverse correlation data. In embodiments, these techniques eliminate or reduce rms noise in a recovered signal peak location by enforcing correlation peak symmetry. The forward and reverse correlation methods described herein may be used for validation of correlation peaks, detection of outlier data points and improved interpolation, such as for higher accuracy localization of a peak center with sub-pixel resolution.

Claims

1. A method of making a correlation between a first image and a second image in an image processing algorithm, comprising:

computing a first correlation using image data associated with the first image as a template and using image data associated with the second image as a search area;

determining a first correlation peak from the first correlation, the first correlation peak representing an image disparity from the first image to the second image;

computing a second correlation using image data associated the second image as a template and using image data associated with the first image as a search area;

determining a second correlation peak from the second correlation, the second correlation peak representing an image disparity from the second image to the first image; and

validating the first correlation peak by comparing the second correlation peak to a threshold value, the threshold value based upon the first correlation peak.

2. The method of claim 1 further comprising combining the first correlation peak with the second correlation peak to determine a combined peak.

3. The method of claim 1 wherein computing a second correlation includes computing the second correlation relative to the first correlation peak.

4. The method of claim 2 wherein combining includes element-by-element averaging of data for the respective correlation peaks.

5. The method of claim 2 wherein combining includes element-by-element multiplication of correlation values.

6. The method of claim 2 wherein combining includes combining correlation tables as if the correlation tables were from the same image data source.

7. The method of claim 2 wherein combining includes interpolating the combined peak using an interpolation function.

8. The method of claim 7 wherein the interpolation function is non-separable in the number of dimensions of the image data.

9. The method of claim 7 wherein the interpolation function is based on an Airy function.

10. The method of claim 7 wherein the interpolation function is based on an actual point spread function.

11. The method of claim 7 wherein the interpolation function is based on a spline.

12. The method of claim 7 wherein the interpolation function is based on a Gaussian distribution.

13. The method of claim 1 further comprising enforcing correlation symmetry by iteratively introducing a fraction offset to at least one of the first image and the second image until symmetry is achieved in a combined correlation peak of the first correlation and the second correlation.

14. A system comprising:

first computing means for computing a first correlation using image data associated with the first image as a template and using image data associated with the second image as a search area;

second computing means for determining a first correlation peak from the first correlation, the first correlation peak representing an image disparity from the first image to the second image;

third computing means for computing a second correlation using image data associated the second image as a template and using image data associated with the first image as a search area;

fourth computing means for determining a second correlation peak from the second correlation, the second correlation peak representing an image disparity from the second image to the first image; and

fifth computing means for validating the first correlation peak by comparing the second correlation peak to a threshold value, the threshold value based upon the first correlation peak.

15. A method of calculating a correlation peak comprising:

determining a forward correlation peak from a forward correlation between a first image and a second image;

determining a reverse correlation peak from a reverse correlation between the second image and the first image;

validating the forward correlation peak;

validating the reverse correlation peak; and

combining the forward correlation peak and the reverse correlation peak to provide a combined correlation peak.

16. The method of claim 15 wherein combining includes element-by-element averaging of data for the forward and reverse correlation peaks.

17. The method of claim 15 wherein combining includes element-by-element multiplication of a plurality of values from the forward correlation and the reverse correlation.

18. The method of claim 15 wherein combining includes combining correlation tables from the forward and reverse correlations as if the correlation tables were from the same image data source.

19. The method of claim 15 wherein combining includes interpolating the combined correlation peak.

20. A system comprising

first computing means for determining a forward correlation peak from a forward correlation between a first image and a second image;

second computing means for determining a reverse correlation peak from a reverse correlation between the second image and the first image;

third computing means for validating the forward correlation peak; and

fourth computing means for combining the forward correlation peak and the reverse correlation peak to provide a combined correlation peak.

21. A method of enforcing correlation peak symmetry between a pair of images in an image processing algorithm, comprising:

determining a forward correlation peak from a forward correlation between a first image and a second image;

determining a reverse correlation peak from a reverse correlation between the second image and the first image;

combining the first correlation peak and the second correlation peak to provide a combined correlation peak; and

enforcing symmetry in the combined correlation peak.

22. The method of claim 21 further comprising determining a plurality of reverse correlation peaks from a plurality of reverse correlations, and combining the first correlation peak and the second correlation peak to provide a combined correlation peak.

23. The method of claim 21 wherein enforcing symmetry includes element-by-element averaging of data for the forward and reverse correlation peaks.

24. The method of claim 21 wherein enforcing symmetry includes element-by-element multiplication of a plurality of values from the forward correlation and the reverse correlation.

25. The method of claim 21 wherein enforcing symmetry includes combining correlation tables from the forward and reverse correlations as if the correlation tables were from the same image data source.

26. The method of claim 21 further comprising enforcing correlation symmetry by iteratively introducing a fraction offset to at least one of the first image and the second image until symmetry is achieved in the combined correlation peak.