Processing sequential video images to detect image motion among interlaced video fields or progressive video images
First Claim
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1. Method for detecting image motion among at least two video images, each image being represented using a plurality of pixels, the method comprising the steps of:
- comparing first information obtained from pixels used to represent a first image with second information obtained from pixels used to represent a second image, to produce a correlation surface representative of image motion;
extracting a motion vector from correlation data included in said correlation surface as a measure of image motion among the at least two images; and
producing a measure of confidence of accuracy with which said motion vector is generated, said measure being determined using a first point on said correlation surface and a second point on said correlation surface, said second point being spaced at least a predetermined distance from said first point on said correlation surface, wherein the step of producing a measure of confidence includes a step of;
producing an average correlation value for each pixel, and wherein the step of producing a measure of confidence includes steps of;
producing an absolute confidence metric as a ratio of a correlation value of the first point on the correlation surface to the average correlation value;
producing a relative confidence metric as a function of a difference between a correlation value of the second point and the correlation value of the first point; and
combining the absolute confidence metric and the relative confidence metric.
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Abstract
Video images are processed to detect image motion among sequential images (e.g., progressive non-interlaced images of a video signal and/or interlaced fields of a video signal), each image being represented using a plurality of pixels. Exemplary embodiments replace block-based motion estimation with pixel-based motion estimation. A correlation surface is generated for every pixel in a reference image, from which a motion vector and confidence metric (i.e., a measure of confidence in the accuracy of the motion vector) are extracted for each pixel.
66 Citations
4 Claims
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1. Method for detecting image motion among at least two video images, each image being represented using a plurality of pixels, the method comprising the steps of:
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comparing first information obtained from pixels used to represent a first image with second information obtained from pixels used to represent a second image, to produce a correlation surface representative of image motion;
extracting a motion vector from correlation data included in said correlation surface as a measure of image motion among the at least two images; and
producing a measure of confidence of accuracy with which said motion vector is generated, said measure being determined using a first point on said correlation surface and a second point on said correlation surface, said second point being spaced at least a predetermined distance from said first point on said correlation surface, wherein the step of producing a measure of confidence includes a step of;
producing an average correlation value for each pixel, and wherein the step of producing a measure of confidence includes steps of;
producing an absolute confidence metric as a ratio of a correlation value of the first point on the correlation surface to the average correlation value;
producing a relative confidence metric as a function of a difference between a correlation value of the second point and the correlation value of the first point; and
combining the absolute confidence metric and the relative confidence metric.
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2. Method for detecting image motion among at least two video images, each image being represented using a plurality of pixels, the method comprising the steps of:
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comparing first information obtained from pixels used to represent a first image with second information obtained from pixels used to represent a second image, to produce a correlation surface representative of image motion;
extracting a motion vector from correlation data included in said correlation surface as a measure of image motion among the at least two images;
producing a measure of confidence of accuracy with which said motion vector is generated, said measure being determined using a first point on said correlation surface and a second point on said correlation surface, said second point being spaced at least a predetermined distance from said first point on said correlation surface; and
identifying whether the motion vector requires filtering by comparing said motion vector to a motion vector of at least one adjacent pixel, wherein the filtering includes steps of;
assigning weighted values to pixels in a neighborhood about a pixel of interest;
comparing a motion vector of one pixel in the neighborhood to motion vectors in remaining pixels of the neighborhood to calculate a weighted measure of the one pixel;
repeating the step of comparing for other predetermined pixels of the neighborhood to calculate plural weighted measures for the neighborhood;
comparing the plural weighted measures; and
selecting a motion vector from the pixel having a highest weighted measure as the motion vector for a pixel of interest in the neighborhood.
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3. Method for processing at least two images to detect image motion among the at least two images, each image being represented using a plurality of pixels, the method comprising the steps of:
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comparing first information obtained from pixels of a first field with second information obtained from pixels of a second field, the second field being temporally separated and spatially nonaligned with respect to the first field, to generate a first correlation surface;
comparing the first information with third information obtained from pixels of a third field, the third field being temporally separated and spatially aligned with the first field, to generate a second correlation surface;
combining said first and second correlation surfaces to produce a composite correlation surface;
extracting a motion vector from correlation data included in said composite correlation surface as a measure of image motion among the at least two video images; and
producing a measure of confidence of accuracy with which said motion vector is generated, wherein the step of producing the measure of confidence includes a step of;
producing an average correlation value for each pixel, and wherein the step of producing the measure of confidence includes steps of;
producing an absolute confidence metric as a ratio of a correlation value of the first point on the correlation surface to the average correlation value;
producing a relative confidence metric as a function of a difference between a correlation value of the second point and the correlation value of the first point; and
combining the absolute confidence metric and the relative confidence metric.
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4. Method for processing at least two images to detect image motion among the at least two images, each image being represented using a plurality of pixels, the method comprising the steps of:
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comparing first information obtained from pixels of a first field with second information obtained from pixels of a second field, the second field being temporally separated and spatially nonaligned with respect to the first field, to generate a first correlation surface;
comparing the first information with third information obtained from pixels of a third field, the third field being temporally separated and spatially aligned with the first field, to generate a second correlation surface;
combining said first and second correlation surfaces to produce a composite correlation surface;
extracting a motion vector from correlation data included in said composite correlation surface as a measure of image motion among the at least two video images; and
identifying whether the motion vector requires filtering by comparing said motion vector to a motion vector of at least one adjacent pixel, wherein the filtering includes steps of;
assigning weighted values to pixels in a neighborhood about a pixel of interest;
comparing a motion vector of one pixel in the neighborhood to motion vectors in remaining pixels of the neighborhood to calculate a weighted measure for the one pixel;
repeating the step of comparing for other predetermined pixels of the neighborhood to calculate plural weighted measures for the neighborhood;
comparing the plural weighted measures; and
selecting a motion vector from the pixel having a highest weighted measure as the motion vector for pixel of interest.
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Specification