from bm3d import bm3d_rgb from experiment_funcs1 import get_experiment_noise, get_psnr, get_cropped_psnr from PIL import Image import argparse import os import torch import numpy as np from torchvision.utils import save_image def main(): imagename = './test_image1/(1271).jpg' save_dir = 'test_result' save_path = 'noise' y = np.array(Image.open(imagename)) / 255 noise_type = 'g3' noise_var = 0.02 seed = 0 noise, psd, kernel = get_experiment_noise(noise_type, noise_var, seed, y.shape) z = np.atleast_3d(y) + np.atleast_3d(noise) y_est = bm3d_rgb(z, psd) psnr = get_psnr(y, y_est) print("PSNR:", psnr) y_est = np.minimum(np.maximum(y_est, 0), 1) z_rang = np.minimum(np.maximum(z, 0), 1) z_rang = torch.from_numpy(np.transpose(z_rang, (2, 0, 1))).float() y_est = torch.from_numpy(np.transpose(y_est, (2, 0, 1))).float() denoise_img_path = os.path.join(save_dir, 'denoised.jpg') save_image(y_est, denoise_img_path) noise_img_path = os.path.join(save_path, 'noise.jpg') save_image(z_rang, noise_img_path) if __name__ == '__main__': main()改为对灰度图处理

可以将代码中的`bm3d_rgb`函数改为`bm3d`函数，同时将读入图像的方式改为读入灰度图像即可。具体代码如下：

from bm3d import bm3d
from experiment_funcs1 import get_experiment_noise, get_psnr, get_cropped_psnr
from PIL import Image
import argparse
import os
import torch
import numpy as np
from torchvision.utils import save_image

def main():
    imagename = './test_image1/(1271).jpg'
    save_dir = 'test_result'
    save_path = 'noise'
    y = np.array(Image.open(imagename).convert('L')) / 255
    noise_type = 'g3'
    noise_var = 0.02
    seed = 0
    noise, psd, kernel = get_experiment_noise(noise_type, noise_var, seed, y.shape)
    z = y + noise
    y_est = bm3d(z, psd)
    psnr = get_psnr(y, y_est)
    print("PSNR:", psnr)
    y_est = np.minimum(np.maximum(y_est, 0), 1)
    z_rang = np.minimum(np.maximum(z, 0), 1)
    z_rang = torch.from_numpy(z_rang).unsqueeze(0).float()
    y_est = torch.from_numpy(y_est).unsqueeze(0).float()
    denoise_img_path = os.path.join(save_dir, 'denoised.jpg')
    save_image(y_est, denoise_img_path)
    noise_img_path = os.path.join(save_path, 'noise.jpg')
    save_image(z_rang, noise_img_path)

if __name__ == '__main__':
    main()