Techniques for image co-registration
Techniques for improving image co-registration. One aspect relates to improving Mutual Information techniques by making the histogram bin widths used therein depend on the amount of signal noise. Another aspect relates to populating the bins by integrating the signal probability in each bin. A third aspect relates to converting top-of-the-atmosphere image data to surface reflectance data, and then using surface reflectance data in the Mutual Information technique for determining a correlation surface. The fourth aspect relates to registering higher-resolution images with lower-resolution images by down-sampling the higher-resolution image. The last aspect relates to a technique for determining the accuracy of the co-registration by synthesizing a perfectly-registered image in a second wavelength band from an image in a first wavelength band and then using Mutual Information between the two images to create a correlation surface.
1. A computer-implemented method for co-registering images, the method comprising:
retrieving at least two images of an area of interest, each of the images being imaged from a different bank of sensors;
creating a signal intensity histogram of each image, with each histogram being divided into a plurality of bins, with each bin having a bin width;
cross correlating the two images by cross correlating the two histograms to create a correlation map that represents Mutual Information in the two images; and
using the peak on the correlation map to register the images with each other;
wherein the width of each bin of each of the two histograms to be cross-correlated, depends on an amount of noise in the signal intensity within that particular bin.
2. A method as defined in claim 1 , wherein the width of each bin increases with increasing signal.
3. A method as defined in claim 1 , wherein the width of each bin is related to the square root of the signal.
4. A method as defined in claim 1 , wherein the bins are populated by integrating a probability of the signal intensity in each bin.
5. A method as defined in claim 1 , further including converting each of the images from top-of-the-atmosphere image data to surface reflectance image data.
6. A method as defined in claim 1 , wherein each of the images includes image data at a different spatial resolution from the other image, so that there is a higher-resolution image and a lower-resolution image.
7. A method as defined in claim 1 , wherein the noise in the signal intensity is based on the shot noise for the corresponding bank of sensors.
8. A method as defined in claim 1 , wherein the width of each bin is based on a common multiplicative constant.
9. A method as defined in claim 1 , wherein the width of each bin is the product of a fixed constant and the signal intensity.
10. A method as defined in claim 1 , wherein the width of each bin is the product of a fixed constant and the square-root of the signal intensity.
11. A method as defined in claim 1 , further comprising using sensor noise to derive Gaussian probability and using the Gaussian probability for the cross correlating.
12. A method as defined in claim 1 , further comprising:
identifying an existence of a high amount of aerosols in the atmosphere; and
populating the bins by integrating a probability of the signal intensity in each bin, wherein the populating is executed in response to the identifying.
13. A method as defined in claim 1 , wherein the width of each bin increases with increasing noise.
14. A method as defined in claim 13 , wherein each of the images includes image data at a different spatial resolution from the other image, so that there is a higher-resolution image and a lower-resolution image.
15. A method as defined in claim 13 , further including converting each of the images from top-of-the-atmosphere image data to surface reflectance image data.
16. A method as defined in claim 13 , wherein the bins are populated by integrating a probability of the signal intensity in each bin.
17. A method as defined in claim 16 , wherein each of the images includes image data at a different spatial resolution from the other image, so that there is a higher-resolution image and a lower-resolution image.
18. A method as defined in claim 16 , further including converting each of the images from top-of-the-atmosphere image data to surface reflectance image data.
19. A method as defined in claim 18 , wherein each of the images includes image data at a different spatial resolution from the other image, so that there is a higher-resolution image and a lower-resolution image.