ADDING GREATER REALISM TO A COMPUTER-GENERATED IMAGE BY SMOOTHING JAGGED EDGES WITHIN THE IMAGE IN AN EFFICIENT MANNER

• US 20190318455A1
• Filed: 03/25/2019
• Published: 10/17/2019
• Est. Priority Date: 04/12/2018
• Status: Active Application

• Current Assignee: NVIDIA Corporation
• Original Assignee: NVIDIA Corporation
• Inventors: Gruen, Holger Heinrich, Marrs, Adam Christopher, Spjut, Josef B., Sathe, Rahul, McGuire, Morgan
• Application Number:
  US16/363,941
• Publication Number:
  US 20190318455A1
• Time in Patent Office: Days
• CPC Class Codes: G06T 15/005 General purpose rendering architectures
• CPC Class Codes: G06T 15/06 Ray-tracing
• CPC Class Codes: G06T 15/503 Blending, e.g. for anti-aliasing
• CPC Class Codes: G06T 2200/28 involving image processing hardware
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 2210/08 Bandwidth reduction
• CPC Class Codes: G06T 2210/21 Collision detection, intersection
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/50 Depth or shape recovery

Abstract

During the rendering of an image, specific pixels in the image are identified where antialiasing would be helpful. Antialiasing is then performed on these identified pixels, where antialiasing is a technique used to add greater realism to a digital image by smoothing jagged edges. This reduces a cost of performing antialiasing by reducing a number of pixels within an image on which antialiasing is performed.

Claims

1. A method comprising:

identifying complex pixels within a scene to be rendered; and

performing antialiasing on each of the complex pixels within the scene, utilizing ray tracing.

2. The method of claim 1, wherein the complex pixels each include visible pixels that are partially covered by one or more instances of geometry within the scene.

3. The method of claim 1, wherein the complex pixels are identified utilizing conservative rasterization.

4. The method of claim 3, wherein the conservative rasterization is implemented over a plurality of passes of one or more instances of geometry within the scene.

5. The method of claim 4, wherein a first pass of the conservative rasterization includes a depth pre-pass.

6. The method of claim 5, wherein the depth pre-pass creates a depth buffer that stores depths for nearest/closest fully covered pixels.

7. The method of claim 4, wherein a second pass of the conservative rasterization includes a pixel identification pass.

8. The method of claim 7, wherein the pixel identification pass identifies and marks the complex pixels, utilizing a pixel shader.

9. The method of claim 1, wherein performing the antialiasing includes determining point-sampling visibility for a sub-pixel area within each of the complex pixels, utilizing GPU ray tracing.

10. The method of claim 1, wherein performing the antialiasing includes, for each of the complex pixels, analytically solving a geometry surface and a coverage of the geometry surface over the complex pixel.

11. The method of claim 1, wherein performing the antialiasing includes evaluating visibility analytically.

12. A system comprising:

a processor that is configured to;

identify complex pixels within a scene to be rendered; and

perform antialiasing on each of the complex pixels within the scene, utilizing ray tracing.

13. The system of claim 12, wherein the complex pixels each include visible pixels that are partially covered by one or more instances of geometry within the scene.

14. The system of claim 12, wherein the complex pixels are identified utilizing conservative rasterization.

15. The system of claim 14, wherein the conservative rasterization is implemented over a plurality of passes of one or more instances of geometry within the scene.

16. The system of claim 15, wherein a first pass of the conservative rasterization includes a depth pre-pass.

17. The system of claim 16, wherein the depth pre-pass creates a depth buffer that stores depths for nearest/closest fully covered pixels.

18. The system of claim 15, wherein a second pass of the conservative rasterization includes a pixel identification pass.

19. The system of claim 18, wherein the pixel identification pass identifies and marks the complex pixels, utilizing a pixel shader.

20. A method comprising:

rendering a non-antialiasing G-buffer for a scene;

identifying visible pixels within the scene that are partially covered by one or more instances of geometry; and

tracing rays through the identified pixels to generate samples for the G-buffer.