README.md

Image Denoising

• Gaussian Image Denoising

• Evaluation
  • Grayscale blind image denoising testing
  • Grayscale non-blind image denoising testing
  • Color blind image denoising testing
  • Color non-blind image denoising testing

• Real Image Denoising

• Evaluation
  • Testing on SIDD dataset
  • Testing on SenseNoise dataset

Gaussian Image Denoising

Evaluation

• Download the pre-trained models and place them in ./pretrained_models/

• Download testsets (Set12, BSD68, CBSD68, Kodak, McMaster, Urban100), run

python download_data.py --data test --noise gaussian

Grayscale image denoising testing (sigma=25)

• To obtain denoised predictions, run

python -u test_gaussian_gray_denoising.py --yml Options/gau_gray_25.yml

Color blind image denoising testing (sigma=50)

python -u test_gaussian_color_denoising.py --yml Options/gau_color_50.yml

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Real Image Denoising

Evaluation

• Download the pre-trained models and place them in ./pretrained_models/

Testing on SIDD dataset

• Download SIDD validation data, run

python download_data.py --noise real --data test --dataset SIDD

• To obtain denoised results, run

python -u test_real_denoising_sidd.py --yml Options/sidd.yml

Testing on SenseNoise dataset

• Download the SenseNoise testing data and place them in ./Datasets/

• To obtain denoised results, run

python test_real_denoising_sense500.py --yml Options/sensenoise.yml