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Noise2Score: Tweedie’s Approach to Self-Supervised Image Denoising without Clean Images

NeurIPS 2021 · Image generation › Image restoration · approach: Self-supervised image denoising · 31 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use AR-DAE score estimation followed by Gaussian Tweedie denoising instead of SURESelf-supervised image denoising · BSD68, Gaussian σ=25, known parametersPSNR (dB): 28.78 -> 29.12Helped
Use AR-DAE score estimation followed by Gaussian Tweedie denoising instead of Noise2VoidSelf-supervised image denoising · BSD68, Gaussian σ=25, known parametersPSNR (dB): 26.77 -> 29.12Helped
Use AR-DAE score estimation followed by Poisson Tweedie denoising instead of PURESelf-supervised image denoising · BSD68, Poisson ζ=0.01, known parametersPSNR (dB): 30.16 -> 30.81Helped
Use AR-DAE score estimation followed by Gamma Tweedie denoising instead of Noise2SelfSelf-supervised image denoising · BSD68, Gamma k=100, known parametersPSNR (dB): 30.49 -> 32.67Helped
Use Noise2Score instead of Noise2SameSelf-supervised image denoising · Confocal MICE, real mixed Poisson-Gaussian noisePSNR (dB): 36.42 -> 36.73Helped
Use Noise2Score rather than Noise2Void when training on Poisson noise ζ=0.01 and testing at varying Poisson levelsSelf-supervised image denoising · BSD68, inference ζ=0.01 to 0.05PSNR (dB): 28.73 vs 30.81; 26.67 vs 29.01; 24.79 vs 28.00; 23.39 vs 27.25; 22.32 vs 26.64Helped

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