From 0da99ac383de21189886a5643a5f232304548720 Mon Sep 17 00:00:00 2001 From: peiszf7yu <3261107288@qq.com> Date: Thu, 21 Jul 2022 20:35:17 +0800 Subject: [PATCH] ADD file via upload --- 频域锐化.py | 143 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 143 insertions(+) create mode 100644 频域锐化.py diff --git a/频域锐化.py b/频域锐化.py new file mode 100644 index 0000000..4e86c19 --- /dev/null +++ b/频域锐化.py @@ -0,0 +1,143 @@ +import numpy as np +import matplotlib.pyplot as plt +import cv2 as cv + + +def ideal_high_filter(img, D0): + #生成一个理想高通滤波器 + h, w = img.shape[:2] + filter_img = np.zeros((h, w)) + u = np.fix(h / 2) + v = np.fix(w / 2) + for i in range(h): + for j in range(w): + d = np.sqrt((i - u) ** 2 + (j - v) ** 2) + filter_img[i, j] = 0 if d < D0 else 1 + return filter_img + + +def butterworth_high_filter(img, D0, rank): + #生成一个巴特沃斯高通滤波器 + h, w = img.shape[:2] + filter_img = np.zeros((h, w)) + u = np.fix(h / 2) + v = np.fix(w / 2) + for i in range(h): + for j in range(w): + d = np.sqrt((i - u) ** 2 + (j - v) ** 2) + filter_img[i, j] = 1 / (1 + (D0 / d) ** (2 * rank)) + return filter_img + + +def exp_high_filter(img, D0, rank): + #生成一个指数高通滤波器 + h, w = img.shape[:2] + filter_img = np.zeros((h, w)) + u = np.fix(h / 2) + v = np.fix(w / 2) + for i in range(h): + for j in range(w): + d = np.sqrt((i - u) ** 2 + (j - v) ** 2) + filter_img[i, j] = np.exp((-1) * (D0 / d) ** rank) + return filter_img + + +def filter_use(img, filter): + #将图像img与滤波器filter结合，生成对应的滤波图像 + # 首先进行傅里叶变换 + f = np.fft.fft2(img) + f_center = np.fft.fftshift(f) + # 应用滤波器进行反变换 + S = np.multiply(f_center, filter) # 频率相乘——l(u,v)*H(u,v) + f_origin = np.fft.ifftshift(S) # 将低频移动到原来的位置 + f_origin = np.fft.ifft2(f_origin) # 使用ifft2进行傅里叶的逆变换 + f_origin = np.abs(f_origin) # 设置区间 + f_origin = f_origin / np.max(f_origin.all()) + return f_origin + + +def DFT_show(img): + #对传入的图像进行傅里叶变换，生成频域图像 + f = np.fft.fft2(img) # 使用numpy进行傅里叶变换 + fshift = np.fft.fftshift(f) # 把零频率分量移到中间 + result = np.log(1 + abs(fshift)) + return result + + +src = cv.imread("da.jpg", 0) +my_img = src.copy() + +# 1.理想高通滤波 +ideal_filter = ideal_high_filter(my_img, D0=40) # 生成理想高通滤波器 +ideal_img = filter_use(my_img, ideal_filter) # 将滤波器应用到图像，生成理想高通滤波图像 +fre_img = DFT_show(my_img) # 原图的频域图像 +fre_ideal_img = DFT_show(ideal_img) # 理想高通滤波图像的频域图像 +plt.figure(dpi=300) +plt.rcParams['font.sans-serif'] = ['SimHei']#用来正常显示中文标签 +plt.subplot(221) +plt.title('原图') +plt.imshow(my_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(222) +plt.title("理想高通滤波图像") +plt.imshow(ideal_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(223) +plt.title('原图频域图') +plt.imshow(fre_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(224) +plt.title("理想高通滤波图像的频域图") +plt.imshow(fre_ideal_img, cmap=plt.cm.gray) +plt.axis("off") +plt.show() + +# 2.巴特沃斯高通滤波器 +my_img = src.copy() +butterworth_filter = butterworth_high_filter(my_img, D0=40, rank=2) # 生成Butterworth高通滤波器 +butterworth_img = filter_use(my_img, butterworth_filter) # 将滤波器应用到图像，生成Butterworth高通滤波图像 +fre_butterworth_img = DFT_show(butterworth_img) # Butterworth高通滤波图像的频域图像 +plt.figure(dpi=300) +plt.rcParams['font.sans-serif'] = ['SimHei']#用来正常显示中文标签 +plt.subplot(221) +plt.title('原图') +plt.imshow(my_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(222) +plt.title("巴特沃斯高通滤波图像") +plt.imshow(butterworth_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(223) +plt.title('原图频域图') +plt.imshow(fre_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(224) +plt.title("巴特沃斯高通滤波图像的频域图") +plt.imshow(fre_butterworth_img, cmap=plt.cm.gray) +plt.axis("off") +plt.show() + +#3.指数高通滤波器 +my_img = src.copy() +exp_filter = exp_high_filter(my_img, D0=40, rank=2) # 生成指数高通滤波器 +exp_img = filter_use(my_img, exp_filter) # 将滤波器应用到图像，生成指数高通滤波图像 +fre_exp_img = DFT_show(exp_img) # 指数高通滤波图像的频域图像 +plt.figure(dpi=300) +plt.rcParams['font.sans-serif'] = ['SimHei']#用来正常显示中文标签 +plt.subplot(221) +plt.title('原图') +plt.imshow(my_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(222) +plt.title("指数高通滤波图像") +plt.imshow(exp_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(223) +plt.title('原图频域图') +plt.imshow(fre_img, cmap=plt.cm.gray) +plt.axis("off") +plt.subplot(224) +plt.title("指数高通滤波图像的频域图") +plt.imshow(fre_exp_img, cmap=plt.cm.gray) +plt.axis("off") +plt.show() \ No newline at end of file