Anisotropic texture filtering by combining results of isotropic filtering at a plurality of sampling points with a gaussian filter

Patent metadata

Field	Value
Publication number	US-12374021-B2
Application number	US-202418635206-A
Country	US
Kind code	B2
Filing date	Apr 15, 2024
Priority date	Jul 26, 2021
Publication date	Jul 29, 2025
Grant date	Jul 29, 2025

Abstract

A method of performing anisotropic texture filtering includes generating one or more parameters describing an elliptical footprint in texture space; performing isotropic filtering at each of a plurality of sampling points along a major axis of the elliptical footprint, wherein a spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η −2 )} units, wherein η is a ratio of a major radius of an ellipse to be sampled and a minor radius of the ellipse to be sampled, wherein the ellipse to be sampled is based on the elliptical footprint; and combining results of the isotropic filtering at the plurality of sampling points with a Gaussian filter to generate at least a portion of a filter result.

First claim

What is claimed is:

1. A method of performing anisotropic texture filtering, the method comprising:
performing isotropic filtering at each of a plurality of sampling points along a major axis of an elliptical footprint in texture space, wherein a spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η −2 )} units, wherein η is a ratio of a major radius of an ellipse to be sampled and a minor radius of the ellipse to be sampled, wherein the ellipse to be sampled is based on the elliptical footprint; and
combining results of the isotropic filtering at the plurality of sampling points with a Gaussian filter to generate at least a portion of a filter result.

2. The method of claim 1 , wherein the spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η −2 )} units by a proportionality factor, the proportionality factor being 1/β, where β is a sampling rate of the Gaussian filter.

3. The method of claim 1 , wherein the spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η −2 )} units by a proportionality factor, the proportionality factor being

1
β

*

η

⌈
η
⌉

,

 where β is a sampling rate of the Gaussian filter.

4. The method of claim 1 , wherein a unit corresponds to the minor radius of the ellipse to be sampled.

5. The method of claim 1 , wherein performing isotropic filtering at each of the plurality of sampling points comprises performing bilinear filtering at each of the plurality of sampling points or performing trilinear filtering at each of the plurality of sampling points.

6. The method of claim 1 , wherein performing isotropic filtering at a sampling point of the plurality of sampling points comprises:
performing a first isotropic filtering at the sampling point at a first mipmap level;
performing a second isotropic filtering at the sampling point at a second mipmap level; and
interpolating between a result of the first isotropic filtering and a result of the second isotropic filtering to generate a result of the isotropic filtering for the sampling point.

7. The method of claim 1 , wherein the ellipse to be sampled is an ellipse defined by the elliptical footprint.

8. The method of claim 1 , wherein performing isotropic filtering at each of the plurality of sampling points comprises performing first isotropic filtering at each sampling point of the plurality of sampling points; and the method further comprises:
performing second isotropic filtering at each of a second plurality of sampling points along the major axis of the elliptical footprint, wherein a spacing between adjacent sampling points of the second plurality of sampling points is proportional to √{square root over (1−η −2 )} units, wherein η is a ratio of a major radius of a second ellipse to be sampled and a minor radius of the second ellipse to be sampled, wherein the second ellipse to be sampled is based on the elliptical footprint;
combining results of the second isotropic filtering; and
interpolating between the combination of the results of the first isotropic filtering and the combination of the results of the second isotropic filtering.

9. The method of claim 8 , wherein the first isotropic filtering is performed at a first mipmap level and the second isotropic filtering is performed at a second mipmap level.

10. The method of claim 8 , wherein the ellipse to be sampled is a higher eccentricity ellipse with respect to the elliptical footprint, and the second ellipse to be sampled is a lower eccentricity ellipse with respect to the elliptical footprint.

11. The method of claim 8 , wherein the ellipse to be sampled has a same eccentricity as the elliptical footprint and is larger than the elliptical footprint, and the second ellipse to be sampled has the same eccentricity as the elliptical footprint and is smaller than the elliptical footprint.

12. The method of claim 1 , wherein the plurality of sampling points are symmetrically positioned about a midpoint of the major axis of the elliptical footprint.

13. The method of claim 1 , wherein the plurality of sampling points comprises N sampling points, wherein N is equal to 2αβ┌η┐, 2α is a width of the Gaussian filter in standard deviations, and β is a sampling rate of the Gaussian filter.

14. The method of claim 1 , wherein a location of the plurality of sampling points is expressed by

(

n
+
ψ

)

⁢

(
κ
)

⁢

1
-

η

-
2

⁢

ρ
-

(

ρ
+

ρ
+

)

 where n is any integer in the half-open interval

[

-

N
2

-
ψ

,

+

N
2

-
ψ

)

,

 ψ is an offset between −1 and 1, the plurality of sampling points comprises N sampling points, the spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η −2 )} units by a proportionality factor κ, ρ − is the minor radius of the ellipse to be sampled, ρ + is the major radius of the ellipse to be sampled and ρ + is a major axis radius vector.

15. The method of claim 1 , further comprising generating one or more parameters describing the elliptical footprint in texture space, wherein the one or more parameters describing the elliptical footprint in texture space comprises one or more of the major axis of the elliptical footprint, a length of the major axis of the elliptical footprint, and a length of a minor axis of the elliptical footprint.

Assignees

• Imagination Tech Ltd

Inventors

• King Rostam
• Rovers Kenneth

Classifications

• G06T7/60

  Analysis of geometric attributes · CPC title

• G06T15/503

  Blending, e.g. for anti-aliasing · CPC title

• G06F17/18

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06T15/04 Primary

  Texture mapping · CPC title