Comments (1)
Hi, @mengchuangji,
Thanks for your interest in our work
We first get noise map by subtracting clean images from noisy images
And we measured standard deviation of noise and covariance between noises within relative positions.
You can follow the definition of correlation with measured std and covariance.
I think this python code might help you to get spatial correlations (note that this code will not be compatible with this codebase)
correlation_sidd.txt
Best
Wooseok Lee
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Related Issues (16)
- Code related issues HOT 4
- whe testing,only pd=2,why does it achieve good denoising performance?
- I wonder how “crop_size” matters?
- Questions about loading data
- 1
- Poor performance HOT 1
- How do I convert the output png image to .mat to upload to SIDDbenchmark for submission?
- about test dataset HOT 1
- About experiment results HOT 2
- About results on SIDD benchmark HOT 1
- About model trained on SIDD Medium and inference on SIDD benchmark HOT 2
- Normalization and preprocessing HOT 4
- Question about the noise correlation HOT 3
- about dataset
- Questions about the hardware configuration of the computer HOT 5
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