import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
# 设置兼容中文
plt.rcParams['font.family'] = ['sans-serif']
plt.rcParams['font.sans-serif'] = ['SimHei']

D:\Anaconda\AZWZ\lib\site-packages\numpy\_distributor_init.py:30: UserWarning: loaded more than 1 DLL from .libs:
D:\Anaconda\AZWZ\lib\site-packages\numpy\.libs\libopenblas.NOIJJG62EMASZI6NYURL6JBKM4EVBGM7.gfortran-win_amd64.dll
D:\Anaconda\AZWZ\lib\site-packages\numpy\.libs\libopenblas.WCDJNK7YVMPZQ2ME2ZZHJJRJ3JIKNDB7.gfortran-win_amd64.dll
  warnings.warn("loaded more than 1 DLL from .libs:\n%s" %

cat = cv.imread('img/cat.jpeg',0)

plt.imshow(cat,cmap=plt.cm.gray)

<matplotlib.image.AxesImage at 0x21b695f0a60>

1.直方图

hist = cv.calcHist([cat],[0],None,[256],[0,256])
hist

array([[  298.],
       [  235.],
       [  379.],
       [  484.],
       [  611.],
       [  541.],
       [  521.],
       [  569.],
       [  643.],
       [  593.],
       [  587.],
       [  583.],
       [  589.],
       [  608.],
       [  653.],
       [  723.],
       [  739.],
       [  745.],
       [  780.],
       [  767.],
       [  820.],
       [  878.],
       [  831.],
       [  887.],
       [  945.],
       [  945.],
       [  994.],
       [  998.],
       [ 1071.],
       [ 1085.],
       [ 1070.],
       [ 1180.],
       [ 1163.],
       [ 1276.],
       [ 1239.],
       [ 1314.],
       [ 1368.],
       [ 1329.],
       [ 1427.],
       [ 1474.],
       [ 1392.],
       [ 1436.],
       [ 1473.],
       [ 1523.],
       [ 1482.],
       [ 1516.],
       [ 1483.],
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       [ 1537.],
       [ 1533.],
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       [ 1752.],
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       [ 2005.],
       [ 2138.],
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       [ 2284.],
       [ 2362.],
       [ 2568.],
       [ 2578.],
       [ 2629.],
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       [ 2662.],
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       [ 3522.],
       [ 3741.],
       [ 3952.],
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       [ 5150.],
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       [ 1362.],
       [ 1292.],
       [ 1325.],
       [ 1276.],
       [ 1161.],
       [ 1118.],
       [  999.],
       [  973.],
       [  896.],
       [  917.],
       [  871.],
       [  819.],
       [  944.],
       [  930.],
       [  941.],
       [  986.],
       [ 1114.],
       [ 1140.],
       [ 1199.],
       [ 1098.],
       [ 1040.],
       [ 1147.],
       [ 1293.],
       [ 1347.],
       [ 1659.],
       [ 1366.],
       [ 1370.],
       [ 1007.],
       [  849.],
       [  765.],
       [  908.],
       [ 1769.],
       [ 3014.]], dtype=float32)

plt.plot(hist)

[<matplotlib.lines.Line2D at 0x21b6a817040>]

2.掩膜的应用

# 创建掩膜对象
mask = np.zeros(cat.shape[:2],np.uint8)
# 指定感兴趣区域
mask[400:650,200:500] = 1

# 蒙版可视化(白色区域即为感兴趣区域)
plt.imshow(mask,cmap=plt.cm.gray)

<matplotlib.image.AxesImage at 0x21b6a84f0d0>

mask_cat = cv.bitwise_and(cat,cat,mask=mask)
plt.imshow(mask_cat,cmap=plt.cm.gray)

<matplotlib.image.AxesImage at 0x21b695816a0>

mask_hist = cv.calcHist([cat],[0],mask,[256],[0,256])

plt.plot(mask_hist)

[<matplotlib.lines.Line2D at 0x21b6a45fa60>]

3.直方图均衡化(提高对比度)

# 对cat图像进行直方图均衡化
dst = cv.equalizeHist(cat)

plt.figure(figsize=(20,20))
plt.subplot(1,2,1)
m1 = plt.imshow(cat,cmap=plt.cm.gray)
plt.title("原图")
plt.subplot(1,2,2)
m2 = plt.imshow(dst,cmap=plt.cm.gray)
plt.title("直方图均衡化后")

Text(0.5, 1.0, '直方图均衡化后')

4.自适应均衡化

#  cv.createCLAHE(对比度限制,每一个小块的大小)
cl = cv.createCLAHE(2.0,(8,8))

# 自适应均衡化
res = cl.apply(cat)

plt.figure(figsize=(20,20))
plt.subplot(1,2,1)
m1 = plt.imshow(cat,cmap=plt.cm.gray)
plt.title("原图")
plt.subplot(1,2,2)
m2 = plt.imshow(res,cmap=plt.cm.gray)
plt.title("自适应均衡化后")

Text(0.5, 1.0, '自适应均衡化后')

总结