python numpy 图象加噪及高斯滤波

问题：

1、imageio.imwrite 能保存np.array为图片 但是保存不了Image.fromarray的图像 找原因

2、有时候需要连起来才能保存图像，找原因

im_salt = Image.fromarray(img1) im_salt = img1.convert('RGB')

3、要系统学习一下numpy的用法

4、code

引用

from PIL import Image import numpy as np from numpy import* from pylab import * import random import imageio

添加高斯噪声

def noise_Gaussian(im,mean,variance): img = np.asarray(im) img1 = img.copy() img1 = np.array(img1/255, dtype=float) noise = np.random.normal(0, 0.05, img1.shape) out = img1 + noise out = np.uint8(out*255) # im_Gaussian = Image.fromarray(out) return out

添加椒盐噪声

def noise_salt(im,persentage): img = np.asarray(im) img1 = img.copy() noiseNum=int(persentage*img1.shape[0]*img1.shape[1]) for i in range(noiseNum): w = random.randint(0,img1.shape[0]-1) h = random.randint(0,img1.shape[1]-1) if random.randint(0,1) ==0: img1[h,w] =0 else: img1[h,w] = 255 im_salt = Image.fromarray(img1) # im_salt = img1.convert('RGB') return im_salt

添加脉冲噪声

def noise_pulse(im,persentage): img = np.asarray(im) img2 = img.copy() noiseNum=int(persentage*img2.shape[0]*img2.shape[1]) for i in range(noiseNum): w = random.randint(0,img2.shape[0]-1) h = random.randint(0,img2.shape[1]-1) img2[h,w] = 255 im_pulse = Image.fromarray(img2) im_pulse = im_pulse.convert('RGB') return im_pulse

高斯滤波器

def gaussian_filter(im, K_size=3, sigma=1.3): img = np.asarray(np.uint8(im)) if len(img.shape) == 3: H, W, C = img.shape else: img = np.expand_dims(img, axis=-1) H, W, C = img.shape ## Zero padding pad = K_size // 2 out = np.zeros((H + pad * 2, W + pad * 2, C), dtype=np.float) out[pad: pad + H, pad: pad + W] = img.copy().astype(np.float) ## prepare Kernel K = np.zeros((K_size, K_size), dtype=np.float) for x in range(-pad, -pad + K_size): for y in range(-pad, -pad + K_size): K[y + pad, x + pad] = np.exp( -(x ** 2 + y ** 2) / (2 * (sigma ** 2))) K /= (2 * np.pi * sigma * sigma) K /= K.sum() tmp = out.copy() # filtering for y in range(H): for x in range(W): for c in range(C): out[pad + y, pad + x, c] = np.sum(K * tmp[y: y + K_size, x: x + K_size, c]) out = np.clip(out, 0, 255) out = out[pad: pad + H, pad: pad + W].astype(np.uint8) return out

main() 添加高斯噪声，并高斯滤波去噪

# 读入图片 img = Image.open("./lena.jpg") im_Gaussian = noise_Gaussian(im,0,0.05) imageio.imwrite("im_Gaussian.jpg",im_Gaussian) im_Gaussian_gaussian = gaussian_filter(im_Gaussian,sigma=1.3) imageio.imwrite("im_Gaussian_gaussian_sigma1.3.jpg",im_Gaussian_gaussian)

添加椒盐噪声，并高斯去噪

im_pulse = noise_pulse(im,0.005) im_pulse = np.asarray(im_pulse) imageio.imwrite("im_pulse.jpg",im_pulse) im_pulse_gaussian = gaussian_filter(im_pulse,sigma=10.3) imageio.imwrite("im_pulse_gaussian_sigma10.3.jpg",im_pulse_gaussian)

添加脉冲噪声，并高斯去噪

im_pulse = noise_pulse(im,0.005) im_pulse = np.asarray(im_pulse) imageio.imwrite("im_pulse.jpg",im_pulse) im_pulse_gaussian = gaussian_filter(im_pulse,sigma=10.3) imageio.imwrite("im_pulse_gaussian_sigma10.3.jpg",im_pulse_gaussian)