1. A method for reducing noise in an image, comprising: receiving a first image as a first set of data formatted according to a red-green-blue (RGB) color model; converting the first set of data 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; denoising the first chrominance channel using modified joint bilateral filtering in a manner that accounts at least for edge information in the luminance channel by calculating a denoised chrominance value for each pixel of the first chrominance channel according to J s C ⁢ ⁢ 1 = ∑ p = Ω ⁢ ⁢ g ⁡ (  p - s  , σ h ) ⁢ g ⁡ ( I p L - I s L , σ i L ) ⁢ I p C ⁢ ⁢ 1 ∑ p = Ω ⁢ ⁢ g ⁡ (  p - s  , σ h ) ⁢ g ⁡ ( I p L - I s L , σ i L ) , where I C1 is the first chrominance channel, Ω is a region of pixels of the first chrominance channel that includes a pixel s, p is a pixel located in the region of pixels Ω, I p C1 is a chrominance value in the first chrominance channel for the pixel p, I p L is a luminance value in the luminance channel for the pixel p, I s L is a luminance value in the luminance channel for the pixel s, J C1 is the denoised first chrominance channel image, J s C1 is the calculated denoised chrominance value of the pixel s, ∥p-s∥ is an Euclidean distance between the pixel p and the pixel s, σ h is a spatial falloff parameter, σ i L is an intensity falloff parameter for the luminance channel, and g( ) is a Gaussian distribution; denoising the second chrominance channel in a manner that accounts at least for edge information in the luminance channel; and converting the luminance channel, the denoised first chrominance channel, and the denoised second chrominance channel to a second set of data formatted according to the RGB color model that is representative of a second image.