IMAGE REGISTRATION USING ROTATION TOLERANT CORRELATION METHOD
First Claim
1. A method for determining similarity between a plurality of signals, comprising:
- selecting a reference data set representing selected characteristics of a defined subject matter;
collecting data to define a target data set, said target data set representing said selected characteristics measured for at least an overlap area of said defined subject matter common to said target data set and said reference data set;
calculating for each one of a plurality of sub-regions within said overlap area, a set of normalized cross-correlation values using said reference data set and said target data set to evaluate a plurality of possible positions of the target data within the reference data;
calculating for said plurality of sub-regions within said overlap area a set of phase correlation values using said reference data set and said target data set to evaluate a plurality of possible position of the target data within the reference data;
calculating an element by element product of the normalized cross-correlation set and the phase correlation set to determine a phase-rho correlation set for each of said plurality of sub-regions within the overlap area;
determining a correlation surface peak location for each sub-region defined by identifying a highest value in the phase-rho correlation set for each sub-region; and
using point sets corresponding to the correlation surface peak locations from selected sub-regions in the overlap area to determine a transformation that minimizes the distance between the reference data set point locations and the corresponding point locations in the target data set to align the target data set with the reference data set;
wherein at least one of said reference data and said target data is selected from the group consisting of image data, rf signal data, and audio data collected by a sensor.
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Abstract
A method for correlating or finding similarity between two data sets. The method can be used for correlating two images with common scene content in order to find correspondence points between the data sets. These correspondence points then can be used to find the transformation parameters which when applied to image 2 brings it into alignment with image 1. The correlation metric has been found to be invariant under image rotation and when applied to corresponding areas of a reference and target image, creates a correlation surface superior to phase and norm cross correlation with respect to the correlation peak to correlation surface ratio. The correlation metric was also found to be superior when correlating data from different sensor types such as from SAR and EO sensors. This correlation method can also be applied to data sets other than image data including signal data.
84 Citations
21 Claims
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1. A method for determining similarity between a plurality of signals, comprising:
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selecting a reference data set representing selected characteristics of a defined subject matter; collecting data to define a target data set, said target data set representing said selected characteristics measured for at least an overlap area of said defined subject matter common to said target data set and said reference data set; calculating for each one of a plurality of sub-regions within said overlap area, a set of normalized cross-correlation values using said reference data set and said target data set to evaluate a plurality of possible positions of the target data within the reference data; calculating for said plurality of sub-regions within said overlap area a set of phase correlation values using said reference data set and said target data set to evaluate a plurality of possible position of the target data within the reference data; calculating an element by element product of the normalized cross-correlation set and the phase correlation set to determine a phase-rho correlation set for each of said plurality of sub-regions within the overlap area; determining a correlation surface peak location for each sub-region defined by identifying a highest value in the phase-rho correlation set for each sub-region; and using point sets corresponding to the correlation surface peak locations from selected sub-regions in the overlap area to determine a transformation that minimizes the distance between the reference data set point locations and the corresponding point locations in the target data set to align the target data set with the reference data set; wherein at least one of said reference data and said target data is selected from the group consisting of image data, rf signal data, and audio data collected by a sensor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer system for determining similarity between a plurality of signals, comprising:
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a least one data store configured for storing a reference data set representing selected characteristics of a defined subject matter, and for storing data which defines a target data set, said target data set representing said selected characteristics measured for at least an overlap area of said defined subject matter common to said target data set and said reference data set; at least one processing device configured to; calculate for each one of a plurality of sub-regions within said overlap area, a set of normalized cross-correlation values using said reference data set and said target data set to evaluate a plurality of possible positions of the target data within the reference data; calculate for said plurality of sub-regions within said overlap area a set of phase correlation values using said reference data set and said target data set to evaluate a plurality of possible position of the target data within the reference data; calculate an element by element product of the normalized cross-correlation set and the phase correlation set to determine a phase-rho correlation set for each of said plurality of sub-regions within the overlap area; determine a correlation surface peak location for each sub-region defined by identifying a highest value in the phase-rho correlation set for each sub-region; and to use point sets corresponding to the correlation surface peak locations from selected sub-regions in the overlap area to determine a transformation that minimizes the distance between the reference data set point locations and the corresponding point locations in the target data set to align the target data set with the reference data set; wherein at least one of said reference data and said target data is selected from the group consisting of image data, rf signal data, and audio data collected by a sensor. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A machine readable media programmed with a set of instructions for determining similarity between a plurality of signals, comprising:
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selecting a reference data set representing selected characteristics of a defined subject matter; collecting data to define a target data set, said target data set representing said selected characteristics measured for at least an overlap area of said defined subject matter common to said target data set and said reference data set; calculating for each one of a plurality of sub-regions within said overlap area, a set of normalized cross-correlation values using said reference data set and said target data set to evaluate a plurality of possible positions of the target data within the reference data; calculating for said plurality of sub-regions within said overlap area a set of phase correlation values using said reference data set and said target data set to evaluate a plurality of possible position of the target data within the reference data; calculating an element by element product of the normalized cross-correlation set and the phase correlation set to determine a phase-rho correlation set for each of said plurality of sub-regions within the overlap area; determining a correlation surface peak location for each sub-region defined by identifying a highest value in the phase-rho correlation set for each sub-region; and using point sets corresponding to the correlation surface peak locations from selected sub-regions in the overlap area to determine a transformation that minimizes the distance between the reference data set point locations and the corresponding point locations in the target data set to align the target data set with the reference data set; wherein at least one of said reference data and said target data is selected from the group consisting of image data, rf signal data, and audio data collected by a sensor.
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20. A method for determining similarity between a plurality of signals, comprising:
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selecting a two-dimensional reference data set representing image data associated with a defined subject matter; collecting data to define a target data set, said target data set representing two dimensional image data for at least an overlap area of said defined subject matter common to said target data set and said reference data set; calculating for each one of a plurality of sub-regions within said overlap area, a set of normalized cross-correlation values using said reference data set and said target data set to evaluate a plurality of possible positions of the target data within the reference data; calculating for said plurality of sub-regions within said overlap area a set of phase correlation values using said reference data set and said target data set to evaluate a plurality of possible position of the target data within the reference data; calculating an element by element product of the normalized cross-correlation set and the phase correlation set to determine a phase-rho correlation set for each of said plurality of sub-regions within the overlap area; determining a correlation surface peak location for each sub-region defined by identifying a highest value in the phase-rho correlation set for each sub-region; and using point sets corresponding to the correlation surface peak locations from selected sub-regions in the overlap area to determine a transformation that minimizes the distance between the reference data set point locations and the corresponding point locations in the target data set to align the target data set with the reference data set. - View Dependent Claims (21)
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Specification