Method and system for object antialiasing in an augmented reality experience
US-2024221129-A1 · Jul 4, 2024 · US
US8965144B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-8965144-B2 |
| Application number | US-201313890132-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 8, 2013 |
| Priority date | Jun 6, 2011 |
| Publication date | Feb 24, 2015 |
| Grant date | Feb 24, 2015 |
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Photon starvation causes streaks and noise and seriously impairs the diagnostic value of the CT imaging. To reduce streaks and noise, a new scheme of adaptive Gaussian filtering relies on the diffusion-derived scale-space concept in one embodiment of the current invention. In scale-space view, filtering by Gaussians of different sizes is similar to decompose the data into a sequence of scales. As the scale measure, the variance of the filter linearly relates to the noise standard deviation of a predetermined noise model in the new filtering method. The new filter has only one optional parameter that remains stable once tuned. Although single-pass processing using the new filter generally achieves desired results, iterations are optionally performed.
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What is claimed is: 1. A method of equally reducing noise in measured signals, comprising the steps of: a) determining a relative value in noise variance at each of the measured signals based upon a function of a predetermined noise model to generate a noise-model based variance; b) automatically generating a discrete filter kernel of a noise-equalizing filter for each of the measured signals based upon the noise-model based variance; and c) applying the discrete filter kernel…
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