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Bin and Drizzle Astrophotography Images

Binning is a process of combining nearby pixels into a single, large pixel. On the plus side is you get a better signal to noise ratio (SNR). On the down side, you lose resolution.

Drizzle flips things around. It expands the resolution of the image by taking 1 pixel and expanding it into 2×2 pixels (of course there is a lot of math involved to make this work well). If your image is under-sampled (when you zoom in on a star, is it blocky?), drizzle can help smooth things out. Drizzle increases resolution but it also increases noise.

What would happen if I did a 2×2 bin and then did a 2×2 drizzle integration? The image resolution would be the same if I skipped both processes. But would the SNR be better? And would the image look better?

The Experiment

I ran through the PixInsight Weighted Batch Preprocessing script on the same set of data (12 images, 10 minutes each, through a hydrogen-alpha filter). The setup was as follows

  • 2×2 binning, no drizzle
  • 2×2 binning, 2×2 drizzle
  • No binning, no drizzle
  • No binning, 2×2 drizzle

The results are as follows (they are not in the correct order as the test cases). Pick 1, 2, 3, 4. Which is better?

Option 1
Option 1
Option 2
Option 2
Option 3
Option 3
Option 4
Option 4

If we zoom into a star, does your preference change?

Zoom Option 1
Zoom Option 1
Zoom Option 2
Zoom Option 2
Zoom Option 3
Zoom Option 3
Zoom Option 4
Zoom Option 4

Assessment

Based on my assessment, I came up with the following preferences

  • Full Image: I think Option 3 and 4 look the best, but that is because there is more contrast.
  • Zoomed Image: I think option 1 is the best, followed by 4. Option 4 is smoother than option 1, but the stars in option 4 are also bigger.

Results

I wanted some real numbers to associate with these images, so I used the PixInsight script Noise Evaluation on each full image. The results were as follows:

BinningDrizzleNoiseCount (%)
1×1No4.033e-0173.18
1×12×22.973e-0136.46
2×2No1.931e-0129.54
2×22×21.369e-0119.34

Based on the numerical analysis from the noise evaluation script, using a 2×2 bin with 2×2 drizzle had the least amount of noise in the samples. But does the data match the visual? Here are the results with the associated tests.

Option 1: Bin 1x1, No Drizzle
Bin 1×1, No Drizzle
Option 2: Bin 1x1, 2x2 Drizzle
Bin 1×1, 2×2 Drizzle
Option 3: Bin 2x2, No Drizzle
Bin 2×2, No Drizzle
Option 4: Bin 2x2, 2x2 Drizzle
Bin 2×2, 2×2 Drizzle
Zoom Option 1: Bin 1x1, No Drizzle
Bin 1×1, No Drizzle
Zoom Option 2: Bin 1x1, 2x2 Drizzle
Bin 1×1, 2×2 Drizzle
Zoom Option 3: Bin 2x2, No Drizzle
Bin 2×2, No Drizzle
Zoom Option 4: Bin 2x2, 2x2 Drizzle
Bin 2×2, 2×2 Drizzle

With the zoomed image, I picked option 1, which has the greatest amount of noise. I felt the details within the image were sharper than my second best result (option 4), which happened to be the image with the least amount of noise.

Caveats

A few notes about this test

  1. To do drizzle effectively, you need a lot of samples. My best results came from 50 or more images. In this scenario, I only had 12 images.
  2. Your results will differ based on your imaging equipment. But with the Weighted Batch Preprocessing script in PixInsight, running your own test is fast.