Comparison of Bayer Interpolation for Very Noisy Images

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.

A Car

Click on the thumbnail for actual size (678kb)

car-chart.png

A Face

Click on the thumbnail for actual size (447kb)

face-chart.png

What I think

This is a quick and dirty experiment but I think VNG gives the images with the least noise.

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4 responses to “Comparison of Bayer Interpolation for Very Noisy Images

  1. Very interesting. There is also four colour VNG interpolation in draw.

  2. Hi, I am studying the Patterned Pixel Grouping (PPG) interpoltation method. but I have some diffcultis in understanding the process of method. May I ask you for some material about the idea or the process of th PPG method? Thank you !

  3. You cannot help, but thanks all the same!

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