多个图片拼接python实现
python实现两张图片的像素融合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 npimport cv2from 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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原文链接：https://blog.csdn.net/weixin_38582851/article/details/80494205