Theres plenty of information around about different methods of Bayer Interpolation. Most of those examples are for images that have very little noise. I wanted to see how different methods would compare for a very noisy image. For example, one that is very underexposed, or shot at a very high ISO setting.
For this experiment I found an image I took at night where the flash on my Fuji S5600 did not fire. I had a 1/10th second exposure so I did get something to work with. I used UFRaw 0.12, converting the image into 8-bit TIFF. I then cropped items of interest and converted to PNG. No noise-reduction was used.
I used the follow methods: Variable Number of Gradients (VNG), Patterned Pixel Grouping (PPG), Adaptive Homogeneity-Directed (AHD) and bilinear.
Click on the thumbnail for actual size (678kb)
Click on the thumbnail for actual size (447kb)
What I think
This is a quick and dirty experiment but I think VNG gives the images with the least noise.