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本文实例为大家分享了python实现两张图片像素融合的具体代码，供大家参考，具体内容如下
通过计算两张图片的颜色直方图特征，利用直方图对图片的颜色进行融合。
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import numpy as np
import cv2
from pil import image,exiftags
def calcmeanandvariance(img):
row=img.shape[0]
col=img.shape[1]
#channel=img.shape[2]
total=row*col
print (row,col,total)
mean=np.zeros((3))
variance=np.zeros((3))
sum=np.zeros((3))
for i in range(row):
for j in range(col):
sum[0]+=img[i][j][0]
sum[1]+=img[i][j][1]
sum[2]+=img[i][j][2]
mean[0]=sum[0]/total
mean[1]=sum[1]/total
mean[2]=sum[2]/total
sum=np.zeros((3))
for i in range(row):
for j in range(col):
sum[0]=np.square(img[i][j][0]-mean[0])
sum[1]=np.square(img[i][j][1]-mean[1])
sum[2]=np.square(img[i][j][2]-mean[2])
variance[0]=np.sqrt(sum[0]/total)
variance[1]=np.sqrt(sum[1]/total)
variance[2]=np.sqrt(sum[2]/total)
print (mean,variance)
return mean,variance
def cololtransit(img1,img2):
image1 = cv2.cvtcolor(img1, cv2.color_bgr2lab)
image2=cv2.cvtcolor(img2, cv2.color_bgr2lab)
mean1,variance1=calcmeanandvariance(image1)
mean2,variance2=calcmeanandvariance(image2)
#print (mean1,variance1)
radio=np.zeros((3))
radio[0]=variance2[0]/variance1[0]
radio[1]=variance2[1]/variance1[1]
radio[2]=variance2[2]/variance1[2]
print('test', radio)
row=image1.shape[0]
col=image1.shape[1]
for i in range(row):
for j in range(col):
image1[i][j][0]=min(255,max(0,radio[0]*(image1[i][j][0]-mean1[0])+mean2[0]))
image1[i][j][1]=min(255,max(0,radio[1]*(image1[i][j][1]-mean1[1])+mean2[1]))
image1[i][j][2]=min(255,max(0,radio[2]*(image1[i][j][2]-mean1[2])+mean2[2]))
image = cv2.cvtcolor(image1, cv2.color_bgr2lab)
return image
if __name__=='__main__':
img1=cv2.imread('1.jpg')
img2=cv2.imread('2.jpg')
cv2.namedwindow('src')
cv2.namedwindow('dst')
#cv2.resizewindow('src',500,500)
#cv2.resizewindow('dst',500,500)
cv2.imshow('src',img1)
cv2.imshow('dst',img2)
cv2.waitkey()
cv2.destroyallwindows()
img=cololtransit(img1,img2)
cv2.namedwindow('result')
cv2.imshow('result',img)
cv2.waitkey()
cv2.destroyallwindows()
#print (img)
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