CBDNet-pytorch

Unofficial PyTorch implementation of CBDNet.

CBDNet in MATLAB

CBDNet in Tensorflow

Update

2020.12.04: We trained the CBDNet model using the dataset in GMSNet. PSNR (DND benchmark): 38.06 -> 39.63.

Quick Start

Download the dataset and pretrained model from GoogleDrive.

Extract the files to data folder and save_model folder as follow:

~/
  data/
    SIDD_train/
      ... (scene id)
    Syn_train/
      ... (id)
    DND/
      images_srgb/
        ... (mat files)
      ... (mat files)
  save_model/
    checkpoint.pth.tar

Train the model:

python train.py

Predict using the trained model:

python predict.py input_filename output_filename

Network Structure

Realistic Noise Model

Given a clean image x, the realistic noise model can be represented as:

Where y is the noisy image, f(.) is the CRF function and the irradiance , M(.) represents the function that convert sRGB image to Bayer image and DM(.) represents the demosaicing function.

If considering denosing on compressed images,

Result