Finish

Filtering_Gaussian_Highpass.py

@@ -6,7 +6,7 @@ plt.rcParams['axes.unicode_minus'] = False
 from Gaussian_Highpass import gaussian_high_pass_filter
 
 # 读取照片
-image_characterTestPattern2 = cv2.imread('file/characterTestPattern2.jpg', 0)  # 改成你自己的图片路径
+image_characterTestPattern2 = cv2.imread('file/characterTestPattern2.jpg', cv2.IMREAD_GRAYSCALE)
 
 # 快速傅里叶变换
 dft_characterTestPattern2 = np.fft.fft2(image_characterTestPattern2)

Filtering_HFE.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+plt.rcParams['font.sans-serif'] = ['simHei']
+plt.rcParams['axes.unicode_minus'] = False
+from High_Frequency_Emphasis import apply_hfe_filter
+
+# 读取照片
+image_boy34 = cv2.imread("file/boy34.jpg", cv2.IMREAD_GRAYSCALE)
+
+# 利用HFE滤波器处理
+k1 = 0.8
+k2 = 0.2
+
+k11 = 0.5
+k22 = 0.5
+
+k111 = 0.2
+k222 = 0.8
+
+image_boy341 = apply_hfe_filter(image_boy34, k1, k2)
+image_boy342 = apply_hfe_filter(image_boy34, k11, k22)
+image_boy343 = apply_hfe_filter(image_boy34, k111, k222)
+
+# 展示图像
+plt.subplot(2,2,1)
+plt.imshow(image_boy34, cmap='gray')
+plt.title('原图')
+plt.axis('off')
+
+plt.subplot(2,2,2)
+plt.imshow(image_boy341, cmap='gray')
+plt.title('HFE滤波器K1=0.8,K2=0.2')
+plt.axis('off')
+
+plt.subplot(2,2,3)
+plt.imshow(image_boy342, cmap='gray')
+plt.title('HFE滤波器K1=0.5,K2=0.5')
+plt.axis('off')
+
+plt.subplot(2,2,4)
+plt.imshow(image_boy343, cmap='gray')
+plt.title('HFE滤波器K1=0.2,K2=0.5')
+plt.axis('off')
+
+plt.tight_layout()
+plt.show()

High_Frequency_Emphasis.py

@@ -0,0 +1,9 @@
+import cv2
+
+def apply_hfe_filter(image, k1, k2):
+
+    high_pass = cv2.Laplacian(image, cv2.CV_64F)
+    high_pass = cv2.convertScaleAbs(high_pass)
+
+    hfe_result = cv2.addWeighted(image, k1, high_pass, k2, 0)
+    return hfe_result