Adaptive Sampling Guided by Multilateral Filtering

• US 20130077893A1
• Filed: 07/31/2012
• Published: 03/28/2013
• Est. Priority Date: 09/23/2011
• Status: Active Grant

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Carr, Nathan A., Moon, Bochang
• Granted Patent: US 8,824,834 B2
• Time in Patent Office: Days
• US Class Current: 382/299
• CPC Class Codes: G06T 15/06 Ray-tracing
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20028 Bilateral filtering
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/10 using non-spatial domain filtering
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

A method, system, and computer-readable storage medium are disclosed for adaptive sampling guided by multilateral filtering. A plurality of versions of a first image are generated. Each of the plurality of versions of the first image has a respective different resolution. A respective priority map is generated for each of the plurality of versions of the first image. Each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the first image. A second image is rendered based on the priority maps. The rendering comprises performing a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the second image than for other regions of the second image.

Claims

1. A computer-implemented method, comprising:

generating a plurality of versions of a first image, wherein each of the plurality of versions of the first image has a respective different resolution;

generating a respective priority map for each of the plurality of versions of the first image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the first image; and

rendering a second image based on the priority maps, comprising performing a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the second image than for other regions of the second image.

2. The method as recited in claim 1, further comprising:

combining each of the priority maps into a global priority map, wherein the global priority map identifies a plurality of high-priority regions in the first image;

wherein rendering the second image based on the priority maps comprises rendering the second image based on the global priority map.

3. The method as recited in claim 2, wherein each respective priority map has a respective resolution of the corresponding one of the plurality of versions of the first image, and wherein the global priority map has a same resolution as the first image.

4. The method as recited in claim 1, wherein generating the plurality of versions of the first image comprises:

using a discrete wavelet transform to decompose the first image into a low-frequency component and a high-frequency component, wherein the low-frequency component comprises a downsampled version of the first image.

5. The method as recited in claim 1, wherein generating the respective priority map for each of the plurality of versions of the first image comprises:

applying a bilateral filter to each of the plurality of versions of the first image.

6. The method as recited in claim 1, further comprising:

generating a plurality of versions of the second image, wherein each of the plurality of versions of the second image has a respective different resolution;

generating a respective priority map for each of the plurality of versions of the second image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the second image; and

rendering a third image based on the priority maps for each of the plurality of versions of the second image, comprising performing a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the third image than for other regions of the third image.

7. The method as recited in claim 1, wherein the second image is reduced in noise compared to the first image.

8. A system, comprising:

at least one processor; and

a memory coupled to the at least one processor, wherein the memory stores program instructions, wherein the program instructions are executable by the at least one processor to;

generate a plurality of versions of a first image, wherein each of the plurality of versions of the first image has a respective different resolution;

generate a respective priority map for each of the plurality of versions of the first image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the first image; and

render a second image based on the priority maps, wherein the program instructions are executable by the at least one processor to perform a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the second image than for other regions of the second image.

9. The system as recited in claim 8, wherein the program instructions are executable by the at least one processor to:

combine each of the priority maps into a global priority map, wherein the global priority map identifies a plurality of high-priority regions in the first image;

wherein, in rendering the second image based on the priority maps, the program instructions are executable by the at least one processor to render the second image based on the global priority map.

10. The system as recited in claim 9, wherein each respective priority map has a respective resolution of the corresponding one of the plurality of versions of the first image, and wherein the global priority map has a same resolution as the first image.

11. The system as recited in claim 8, wherein, in generating the plurality of versions of the first image, the program instructions are executable by the at least one processor to:

use a discrete wavelet transform to decompose the first image into a low-frequency component and a high-frequency component, wherein the low-frequency component comprises a downsampled version of the first image.

12. The system as recited in claim 8, wherein, in generating the respective priority map for each of the plurality of versions of the first image, the program instructions are executable by the at least one processor to:

apply a bilateral filter to each of the plurality of versions of the first image.

13. The system as recited in claim 8, wherein the program instructions are executable by the at least one processor to:

generate a plurality of versions of the second image, wherein each of the plurality of versions of the second image has a respective different resolution;

generate a respective priority map for each of the plurality of versions of the second image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the second image; and

render a third image based on the priority maps for each of the plurality of versions of the second image, wherein the program instructions are executable by the at least one processor to perform a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the third image than for other regions of the third image.

14. The system as recited in claim 8, wherein the second image is reduced in noise compared to the first image.

15. A computer-readable storage medium storing program instructions computer-executable to perform:

generating a plurality of versions of a first image, wherein each of the plurality of versions of the first image has a respective different resolution;

generating a respective priority map for each of the plurality of versions of the first image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the first image; and

rendering a second image based on the priority maps, comprising performing a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the second image than for other regions of the second image.

16. The computer-readable storage medium as recited in claim 15, further comprising:

combining each of the priority maps into a global priority map, wherein the global priority map identifies a plurality of high-priority regions in the first image;

wherein rendering the second image based on the priority maps comprises rendering the second image based on the global priority map.

17. The computer-readable storage medium as recited in claim 16, wherein each respective priority map has a respective resolution of the corresponding one of the plurality of versions of the first image, and wherein the global priority map has a same resolution as the first image.

18. The computer-readable storage medium as recited in claim 15, wherein generating the plurality of versions of the first image comprises:

using a discrete wavelet transform to decompose the first image into a low-frequency component and a high-frequency component, wherein the low-frequency component comprises a downsampled version of the first image.

19. The computer-readable storage medium as recited in claim 15, wherein generating the respective priority map for each of the plurality of versions of the first image comprises:

applying a bilateral filter to each of the plurality of versions of the first image.

20. The computer-readable storage medium as recited in claim 15, further comprising:

generating a plurality of versions of the second image, wherein each of the plurality of versions of the second image has a respective different resolution;

generating a respective priority map for each of the plurality of versions of the second image, wherein each respective priority map identifies a plurality of high-priority regions in a corresponding one of the plurality of versions of the second image; and

rendering a third image based on the priority maps for each of the plurality of versions of the second image, comprising performing a ray-tracing process having a greater number of samples per pixel for the high-priority regions of the third image than for other regions of the third image.