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eastmountyxz · web-flow · commit 70fe01ab1fcc · 2021-08-20T17:34:47.000+08:00
diff --git a/blog44-ImageProcessingSummary/ImageProcessing_13_morphology.py b/blog44-ImageProcessingSummary/ImageProcessing_13_morphology.py
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+#encoding:utf-8
+#By:Eastmount CSDN 2021-08-20
+import cv2  
+import numpy as np
+import matplotlib.pyplot as plt
+
+#读取图片
+src = cv2.imread('na.png', cv2.IMREAD_UNCHANGED)
+img = cv2.cvtColor(src,cv2.COLOR_BGR2RGB)
+
+# 转化为灰度图
+Grayimg = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+
+# 1、消除椒盐噪声：
+# 中值滤波器
+median = cv2.medianBlur(Grayimg, 5)
+# 消除噪声图
+cv2.imshow("median-image", median)
+
+# 2、直方图均衡化：
+equalize = cv2.equalizeHist(median)
+cv2.imshow('hist', equalize)
+
+# 3、二值化处理：
+# 阈值为140
+ret, binary = cv2.threshold(equalize, 127, 255,cv2.THRESH_BINARY)
+cv2.imshow("binary-image",binary)
+cv2.waitKey(0)
+
+#设置卷积核
+kernel = np.ones((10,10), np.uint8)
+close = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel)
+
+#图像开运算
+kernel = np.ones((10,10), np.uint8) 
+open1 = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
+
+#显示图像
+cv2.imshow("src", src)
+cv2.imshow("result", close)
+
+#等待显示
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+
+#图像开运算
+kernel = np.ones((10,10), np.uint8) 
+gradient = cv2.morphologyEx(binary, cv2.MORPH_GRADIENT, kernel)
+
+# Sobel算子 XY方向求梯度 cv2.CV_8U
+x = cv2.Sobel(close, cv2.CV_32F, 1, 0, ksize = 3) #X方向
+y = cv2.Sobel(close, cv2.CV_32F, 0, 1, ksize = 3) #Y方向
+#absX = cv2.convertScaleAbs(x)   # 转回uint8    
+#absY = cv2.convertScaleAbs(y)
+#Sobel = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
+gradient = cv2.subtract(x, y)
+sobel = cv2.convertScaleAbs(gradient)
+cv2.imshow('Sobel', sobel)
+cv2.waitKey(0)
+
+#循环显示图形
+titles = [ 'source', 'gray', 'median', 'equalize', 'binary', 'close', 'open', 'gradient', 'sobel']  
+images = [img, Grayimg, median, equalize, binary, close, open1, gradient, sobel]  
+for i in range(9):  
+   plt.subplot(3, 3, i+1), plt.imshow(images[i], 'gray')  
+   plt.title(titles[i])  
+   plt.xticks([]),plt.yticks([])  
+plt.show()  
