def add_pepper_noise(img_path):
"""
给图片添加椒盐噪声
"""
image, x, y = read_image(img_path)
for i in range(x):
for j in range(y):
pixel = image.getpixel((i, j))
if random.random() > 0.99:
image.putpixel((i, j), 255 if random.random() > 0.5 else 0)
else:
image.putpixel((i, j), pixel)
return image
def add_gaussian_noise(img_path):
"""
给图片添加高斯噪声
"""
image, x, y = read_image(img_path)
gaussian_noise = 30 * np.random.normal(0, 1, (x, y))
for i in range(x):
for j in range(y):
pixel = image.getpixel((i, j))
if random.random() > 0.99:
new_pixel = int(gaussian_noise[i, j] + pixel)
image.putpixel((i, j), new_pixel)
else:
image.putpixel((i, j), pixel)
return image
from Gray import read_image
import math
image, x, y = read_image('c.png')
table = []
for i in range(256):
table.append(40 * math.log1p(i))
image = image.point(table, 'L')
image.save('c_log.png')
from Gray import read_image
image,x,y=read_image('b.png')
table=[]
for i in range(256):
table.append(i**0.5)
image=image.point(table,'L')
image.save('b_pow.png')
from Gray import read_image
import pandas as pd
import matplotlib.pyplot as plt
image, x, y = read_image('e.png')
pixels = []
for i in range(x):
for j in range(y):
pixel = image.getpixel((i, j))
pixels.append((pixel))
pixels = pd.Series(pixels)
proportitionDict = dict(pixels.value_counts(normalize=True))
hist_dict = {}
add = 0
for i in range(256):
if i in proportitionDict.keys():
add += proportitionDict[i]
hist_dict[i] = add
table = []
for i in range(256):
table.append(hist_dict[i] * 255)
print(table)
image = image.point(table, 'L')
image.show()
image.save('e_hist.png')
from Gray import read_image
import pandas as pd
import matplotlib.pyplot as plt
# 原图
image,x,y=read_image('g.png')
pixels=[]
for i in range(x):
for j in range(y):
pixel=image.getpixel((i,j))
pixels.append((pixel))
pixels=pd.Series(pixels)
proportitionDict=dict(pixels.value_counts(normalize=True))
hist_dict={}
add=0
for i in range(256):
if i in proportitionDict.keys():
add+=proportitionDict[i]
hist_dict[i]=add
table=[]
for i in range(256):
table.append(hist_dict[i]*255)
plt.subplot(221)
plt.hist(pixels,bins=256)
# 目标图片
from Gray import read_image
image, x, y = read_image('a.png')
for i in range(x):
for j in range(y):
pixel = image.getpixel((i, j))
image.putpixel((i, j), 255 - pixel)
image.save('a_neg.png')