该功能会在图像中添加高斯，椒盐，泊松和斑点噪声
Parameters----------image : ndarray Input image data. Will be converted to float.mode : str One of the following strings, selecting the type of noise to add: 'gauss' Gaussian-distributed additive noise. 'poisson' Poisson-distributed noise generated from the data. 's&p' Replaces random pixels with 0 or 1. 'speckle' Multiplicative noise using out = image + n*image,where n is uniform noise with specified mean & variance.import numpy as npimport osimport cv2def noisy(noise_typ,image): if noise_typ == "gauss": row,col,ch= image.shape mean = 0 var = 0.1 sigma = var**0.5 gauss = np.random.normal(mean,sigma,(row,col,ch)) gauss = gauss.reshape(row,col,ch) noisy = image + gauss return noisy elif noise_typ == "s&p": row,col,ch = image.shape s_vs_p = 0.5 amount = 0.004 out = np.copy(image) # Salt mode num_salt = np.ceil(amount * image.size * s_vs_p) coords = [np.random.randint(0, i - 1, int(num_salt)) for i in image.shape] out[coords] = 1 # Pepper mode num_pepper = np.ceil(amount* image.size * (1. - s_vs_p)) coords = [np.random.randint(0, i - 1, int(num_pepper)) for i in image.shape] out[coords] = 0 return out elif noise_typ == "poisson": vals = len(np.unique(image)) vals = 2 ** np.ceil(np.log2(vals)) noisy = np.random.poisson(image * vals) / float(vals) return noisy elif noise_typ =="speckle": row,col,ch = image.shape gauss = np.random.randn(row,col,ch) gauss = gauss.reshape(row,col,ch) noisy = image + image * gauss return noisy
