Abstract: Noise in an image is reduced in a manner that takes into account edge information in one or more channels of the image. A first image is received that is formatted according to a red-green-blue (RGB) color model. The first image is converted from the RGB color model to a second color model that includes at least a luminance channel, a first chrominance channel, and a second chrominance channel that are representative of the first image. The first and second chrominance channels are each denoised in a manner that accounts at least for edge information in the luminance channel, and may also include edge information from other channels in a manner that accounts for per-channel noise characteristics. The luminance channel and denoised first and second chrominance channels are converted to a second image formatted according to the RGB color model that is a noise-reduced version of the first image.

Abstract: Noise in an image is reduced in a manner that takes into account edge information in one or more channels of the image. A first image is received that is formatted according to a red-green-blue (RGB) color model. The first image is converted from the RGB color model to a second color model that includes at least a luminance channel, a first chrominance channel, and a second chrominance channel that are representative of the first image. The first and second chrominance channels are each denoised in a manner that accounts at least for edge information in the luminance channel, and may also include edge information from other channels in a manner that accounts for per-channel noise characteristics. The luminance channel and denoised first and second chrominance channels are converted to a second image formatted according to the RGB color model that is a noise-reduced version of the first image.