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Contrast.py
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Contrast.py
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from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
class colortrast:
def histeq(self,img,nbr_bins=256):
im=img.copy()
times = np.bincount(im.flatten(), minlength=255) # 计算各灰度级出现次数
freq = times / (im.size) # 计算出现频率
accumu = freq.cumsum(axis=0) # 累加频率
for idx, pixel in enumerate(im):
im[idx] = np.uint8(accumu[pixel] * 255 + 0.5)
return im.reshape(im.shape).astype('uint8')
def histeq1(self,img):
im=img.copy()
H,W,_=im.shape
r=self.histeq(im[:,:,0]).flatten()
g = self.histeq(im[:, :, 1]).flatten()
b = self.histeq(im[:, :, 2]).flatten()
im=np.column_stack((r,g,b))
im.resize(H,W,3)
return im.astype('uint8')
def linear_contrast_stretch(self,fa,ga,fb,gb,im):
im2=im.copy()
H,W,_=im2.shape
k1=ga/fa
k2=(gb-ga)/(fb-fa)
k3=(255-gb)/(255-fb)
for row in range(H):
for col in range(W):
for i in range(3):
if im2[row][col][i] < fa:
im2[row][col][i] = im2[row][col][i] * k1
elif im2[row][col][i] > fb:
im2[row][col][i] = (im2[row][col][i] - fb) * k3 + gb
else:
im2[row][col][i] = (im2[row][col][i] - fa) * k2 + ga
return im2.astype('uint8')
img=Image.open('/home/wlj/pic/6.jpg')
img=np.array(img)
plt.figure()
plt.subplot(421)
plt.title('origin')
plt.axis('off')
plt.imshow(img)
plt.subplot(422)
arr=img.flatten()
plt.hist(arr, bins=256, normed=1, facecolor='red', alpha=0.75)
plt.subplot(423)
plt.title('linear')
plt.axis('off')
t=colortrast()
im2=t.linear_contrast_stretch(70,20,180,230,img)
plt.imshow(im2)
plt.subplot(424)
arr2=im2.flatten()
plt.hist(arr2, bins=256, normed=1, facecolor='red', alpha=0.75)
plt.subplot(425)
plt.axis('off')
plt.title('histrgb')
im3=t.histeq1(img)
plt.imshow(im3)
plt.subplot(426)
arr3=im3.flatten()
plt.hist(arr3, bins=256, normed=1, facecolor='red', alpha=0.75)
plt.subplot(427)
plt.axis('off')
plt.title('hist')
im4=t.histeq(img)
plt.imshow(im4)
plt.subplot(428)
arr4=im4.flatten()
plt.hist(arr4, bins=256, normed=1, facecolor='red', alpha=0.75)
plt.show()