日韩性视频-久久久蜜桃-www中文字幕-在线中文字幕av-亚洲欧美一区二区三区四区-撸久久-香蕉视频一区-久久无码精品丰满人妻-国产高潮av-激情福利社-日韩av网址大全-国产精品久久999-日本五十路在线-性欧美在线-久久99精品波多结衣一区-男女午夜免费视频-黑人极品ⅴideos精品欧美棵-人人妻人人澡人人爽精品欧美一区-日韩一区在线看-欧美a级在线免费观看

歡迎訪問 生活随笔!

生活随笔

當前位置: 首頁 > 编程资源 > 编程问答 >内容正文

编程问答

五、像素运算

發布時間:2023/12/1 编程问答 26 豆豆
生活随笔 收集整理的這篇文章主要介紹了 五、像素运算 小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

一、相關概念

1、算術運算
Ⅰ加減乘除
Ⅱ調節亮度
Ⅲ調整對比度

2、邏輯運算
Ⅰ與或非
Ⅱ遮罩層控制

二、圖像算術運算(加減乘除均值方差)

其中圖像的加減乘除需要保證兩張圖像的大小相同

import cv2 import numpy as npdef add(src1,src2):dst = cv2.add(src1,src2)cv2.imshow("add",dst)def subtract(src1,src2):dst1 = cv2.subtract(src1,src2)dst2 = cv2.subtract(src2,src1)cv2.imshow("subtract1",dst1)cv2.imshow("subtract2",dst2)def divide(src1,src2):dst1 = cv2.divide(src1,src2)dst2 = cv2.divide(src2,src1)cv2.imshow("divide1",dst1)cv2.imshow("divide2",dst2)def multiply(src1,src2):dst = cv2.multiply(src1,src2)cv2.imshow("multiply",dst)def average_value(src1,src2):#圖像均值m1 = cv2.mean(src1)m2 = cv2.mean(src2)print("均值1:",m1)print("均值2:",m2)def mean_variance(src1,src2):m1,dev1 = cv2.meanStdDev(src1)#m為均值,dev為方差m2,dev2 = cv2.meanStdDev(src2)print("均值1:",m1)print("均值2:",m2)print("方差1:",dev1)print("方差2:",dev2)def compare(src1):#當全為1的圖像,其方差為0h,w = src1.shape[:2]print(h,w)img = np.ones([h,w],np.uint8)m,dev = cv2.meanStdDev(img)print("均值是:",m,"方差是:",dev)src1 = cv2.imread(r"G:\Juptyer_workspace\study\opencv\opencv3\a1.jpg") src2 = cv2.imread(r"G:\Juptyer_workspace\study\opencv\opencv3\a2.jpg") print(src1.shape) print(src2.shape)#cv2.namedWindow("image1",cv2.WINDOW_AUTOSIZE) cv2.imshow("image1",src1) cv2.imshow("image2",src2)add(src1,src2) subtract(src1,src2) divide(src1,src2) multiply(src1,src2)average_value(src1,src2) mean_variance(src1,src2)compare(src1)cv2.waitKey(0) cv2.destroyAllWindows()

運行效果如下:

三、圖像的邏輯運算(與或非)

與或運算針對兩張圖片而言,非運算針對單一圖片而言

import cv2 import numpy as npdef logic(src1,src2):And = cv2.bitwise_and(src1,src2)cv2.imshow("logic_and",And)Or = cv2.bitwise_or(src1,src2)cv2.imshow("logic_or",Or)Not1 = cv2.bitwise_not(src1)cv2.imshow("logic_not1",Not1)Not2 = cv2.bitwise_not(src2)cv2.imshow("logic_not2",Not2)src1 = cv2.imread(r"G:\Juptyer_workspace\study\opencv\opencv3\a1.jpg") src2 = cv2.imread(r"G:\Juptyer_workspace\study\opencv\opencv3\a2.jpg") cv2.imshow("image1",src1) cv2.imshow("image2",src2)logic(src1,src2)cv2.waitKey(0) cv2.destroyAllWindows()

運行效果圖如下:

四、對圖像的對比度、亮度進行調節

import cv2 import numpy as npdef contrast_brightness(src,c,b):#目標圖像、對比度、亮度h,w,ch = src.shapeblack = np.zeros([h,w,ch],src.dtype)dst = cv2.addWeighted(src,c,black,1-c,b)cv2.imshow("contrast_brightness",dst)src = cv2.imread(r"G:\Juptyer_workspace\study\opencv\opencv3\a1.jpg") cv2.imshow("image",src)contrast_brightness(src,1,2)cv2.waitKey(0) cv2.destroyAllWindows()

效果圖如下:

總結

以上是生活随笔為你收集整理的五、像素运算的全部內容,希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯,歡迎將生活随笔推薦給好友。