US 10,096,088 B2 · Robust regression method for image-space denoising

Abstract

The disclosure provides an approach for denoising (also referred to as “filtering”) rendered images. In one embodiment, a denoising application takes as input rendered images and feature buffers that encode image information such as surface positions, surface depths, surface normals, surface albedos, and distances to the camera. For each pixel in a received image, the denoising application performs a first-order regression in a predefined neighborhood of the pixel to find a linear combination of pixel features that fits pixel colors in the predefined neighborhood. In such a first-order regression, the local regression weight of each pixel in the neighborhood may be determined using a metric which computes distances based on color values in patches around pixels being compared. In another embodiment, collaborative filtering may be performed in which filtered output from the first-order regression in each neighborhood is averaged with filtered output from overlapping neighborhoods to obtain a final output.

Claims20

Dependent claims

A computer-implemented method for denoising a rendered image, comprising:

receiving the rendered image and a set of features associated with the rendered image;
for each pixel of a plurality of pixels in the rendered image, performing a regression in a predefined neighborhood of the pixel to find a combination of pixel features that fits pixel colors in the predefined neighborhood, wherein, in the regression, a respective local regression weight associated with each pixel in the predefined neighborhood is determined based, at least in part, on a distance metric which computes distances based, at least in part, on color values in patches around pixels being compared;
and
determining a respective output color value for each pixel of a plurality of pixels in a denoised image corresponding to a respective one of the plurality of pixels in the rendered image based, at least in part, on the fittings produced by a plurality of the regressions.

1 more element

A non-transitory computer-readable storage medium storing instructions, which when executed by a computer system, perform operations for denoising a rendered image, the operations comprising:

receiving the rendered image and a set of features associated with the rendered image;
for each pixel of a plurality of pixels in the rendered image, performing a regression in a predefined neighborhood of the pixel to find a combination of pixel features that fits pixel colors in the predefined neighborhood, wherein, in the regression, a respective local regression weight associated with each pixel in the predefined neighborhood is determined based, at least in part, on a distance metric which computes distances based, at least in part, on color values in patches around pixels being compared;
and
determining a respective output color value for each pixel of a plurality of pixels in a denoised image corresponding to a respective one of the plurality of pixels in the rendered image based, at least in part, on the fittings produced by a plurality of the regressions.

1 more element

Dependencies are inferred from the claim text.

Robust regression method for image-space denoising

Life of this patent

Robust regression method for image-space denoising

Life of this patent

Abstract

Claims20