• 使用Python-OpenCV向图片添加噪声(高斯噪声、椒盐噪声)


    在matlab中,存在执行直接得函数来添加高斯噪声和椒盐噪声。Python-OpenCV中虽然不存在直接得函数,但是很容易使用相关的函数来实现。

    代码:

    import numpy as np
    import random
    import cv2
    
    def sp_noise(image,prob):
        '''
        添加椒盐噪声
        prob:噪声比例 
        '''
        output = np.zeros(image.shape,np.uint8)
        thres = 1 - prob 
        for i in range(image.shape[0]):
            for j in range(image.shape[1]):
                rdn = random.random()
                if rdn < prob:
                    output[i][j] = 0
                elif rdn > thres:
                    output[i][j] = 255
                else:
                    output[i][j] = image[i][j]
        return output
    
    
    def gasuss_noise(image, mean=0, var=0.001):
        ''' 
            添加高斯噪声
            mean : 均值 
            var : 方差
        '''
        image = np.array(image/255, dtype=float)
        noise = np.random.normal(mean, var ** 0.5, image.shape)
        out = image + noise
        if out.min() < 0:
            low_clip = -1.
        else:
            low_clip = 0.
        out = np.clip(out, low_clip, 1.0)
        out = np.uint8(out*255)
        #cv.imshow("gasuss", out)
        return out

    可见,只要我们得到满足某个分布的多维数组,就能作为噪声添加到图片中。

    例如:

    import cv2
    import numpy as np
    
    >>> im = np.empty((5,5), np.uint8) # needs preallocated input image
    >>> im
    array([[248, 168,  58,   2,   1],  # uninitialized memory counts as random, too ?  fun ;) 
           [  0, 100,   2,   0, 101],
           [  0,   0, 106,   2,   0],
           [131,   2,   0,  90,   3],
           [  0, 100,   1,   0,  83]], dtype=uint8)
    >>> im = np.zeros((5,5), np.uint8) # seriously now.
    >>> im
    array([[0, 0, 0, 0, 0],
           [0, 0, 0, 0, 0],
           [0, 0, 0, 0, 0],
           [0, 0, 0, 0, 0],
           [0, 0, 0, 0, 0]], dtype=uint8)
    >>> cv2.randn(im,(0),(99))         # normal
    array([[  0,  76,   0, 129,   0],
           [  0,   0,   0, 188,  27],
           [  0, 152,   0,   0,   0],
           [  0,   0, 134,  79,   0],
           [  0, 181,  36, 128,   0]], dtype=uint8)
    >>> cv2.randu(im,(0),(99))         # uniform
    array([[19, 53,  2, 86, 82],
           [86, 73, 40, 64, 78],
           [34, 20, 62, 80,  7],
           [24, 92, 37, 60, 72],
           [40, 12, 27, 33, 18]], dtype=uint8)

    然后再:

    img = ...
    noise = ...
    
    image = img + noise

    参考链接:

    1、https://stackoverflow.com/questions/22937589/how-to-add-noise-gaussian-salt-and-pepper-etc-to-image-in-python-with-opencv#

    2、https://stackoverflow.com/questions/14435632/impulse-gaussian-and-salt-and-pepper-noise-with-opencv#

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  • 原文地址:https://www.cnblogs.com/lfri/p/10627595.html
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