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The image motion estimate is then.
If the same feature value can be found at many image positions, the motion estimate is very ambiguous as many corresponding matches can be found, leading to a huge number of hypotheses that are hardly reliable.
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Finally the horizontal and vertical components of the subpixel accurate motion estimate are obtained by computing the location of the maxima of each of the above fitted quadratics.
The apparent non-linear nature of the vertical motion, coupled with long-period GPS errors, implies that the quality of the seafloor motion estimates is not uniform over the 20-yr period.
The motion estimates are computed in a sound probabilistic framework by performing inference on a probabilistic graphical model.
Our focus is on minimizing spatial blurring, restricting to temporal filtering when motion estimates are reliable, and spatially shrinking only insignificant coefficients when the motion is unreliable.
Head motion estimates were derived from the MR data and used to correct the PET data in LOR space before image reconstruction [1].
By implementing the proposed validation method, our SR approach was able to show robust HR image reconstruction results, even when the motion estimates were not accurate at the sub-pixel level.
Regions without motion estimates are classified as occlusion regions.
After optimization, the motion estimates are used to construct registered and motion corrected volumes.
In comparison, traditional accounts assume that motion estimates are based on sensory signals alone.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com