python - 根据像素值向图像添加噪声

Question

我想根据百分比为灰度图像添加高斯噪声

我想将眼睛区域中任何像素强度值的 5% 作为噪声添加到整个图像中，所以我想要做的是选择眼睛区域内的任何像素并给定它们的简单像素强度添加 5% 的高斯噪声到整个图像。

def generate_noisy_image(x, variance):
    noise = np.random.normal(0, variance, (1, x.shape[0]))
    return x + noise

def loadimage(path):
    filepath_list = listdir(path)
    for filepath in filepath_list:
        img = Image.open(path + filepath)
        img = img.resize((81, 150))
        img = np.asarray(img)
        generate_noisy_image(img, 0.025)
        img = Image.fromarray(img)
        img.save('C:/Users/noisy-images/'+filepath, 'JPEG')



loadimage('C:/Users/my_images/')

ValueError：操作数无法与形状一起广播 (150,81) (1,150)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-96-1bebb687f5e7> in <module>
     11 
     12 
---> 13 loadimage('source path from images')
     14 

<ipython-input-96-1bebb687f5e7> in loadimage(path)
      5         img = img.resize((81, 150))
      6         img = np.asarray(img)
----> 7         generate_noisy_image(img, 0.025)
      8         print(generate_noisy_image.shape)
      9         img = Image.fromarray(img)

<ipython-input-95-7cc3346953f6> in generate_noisy_image(x, variance)
      1 def generate_noisy_image(x, variance):
      2     noise = np.random.normal(0, variance, (1, x.shape[0]))
----> 3     return x + noise

Answer 1

非常基本的示例，破解np.array's dims 以使其工作。

import numpy as np


def generate_noisy_image(x: np.array, variance: float) -> np.array:
    noise = np.random.normal(loc=0, scale=variance, size=x.shape)
    return x + noise


if __name__ == "__main__":
    img_2D = np.random.random(size=(81, 150))
    img_2D_fake = generate_noisy_image(x=img_2D, variance=0.05)

    var = np.var(img_2D_fake - img_2D)
    sigma_by_var = var ** 0.5

    sigma = np.std(img_2D_fake - img2D)


    print(f"variance={var}\nsigma_by_var={sigma_by_var}\nsigma={sigma}")

请记住，标准推导是方差的平方根。在上面的例子中，它应该打印一个 var ~0.0025 和一个 std ~0.05。