完成傅里叶变换后的频率幅度和相位角的重组

Woman_Square.py

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+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+plt.rcParams['font.sans-serif'] = ['simHei']
+plt.rcParams['axes.unicode_minus'] = False
+
+#读取照片
+image_woman = cv2.imread("file/woman.jpg", cv2.IMREAD_GRAYSCALE)
+image_square = cv2.imread("file/square.jpg", cv2.IMREAD_GRAYSCALE)
+
+#进行快速傅里叶变换获取频谱幅度和相位角
+dft_woman = np.fft.fft2(image_woman)
+sm_woman = np.abs(dft_woman)
+pa_woman = np.angle(dft_woman)
+
+dft_square = np.fft.fft2(image_square)
+sm_square = np.abs(dft_square)
+pa_square = np.angle(dft_square)
+
+#利用频谱幅度和相位角重构图像
+image_woman_square_dft = np.multiply(sm_woman, np.exp(1j*pa_square))
+image_woman_square = np.abs(np.fft.ifft2(image_woman_square_dft))
+
+image_square_woman_dft = np.multiply(sm_square, np.exp(1j*pa_woman))
+image_square_woman = np.abs(np.fft.ifft2(image_square_woman_dft))
+
+#将woman频谱幅度的最亮点移到中心
+shift_woman = np.fft.fftshift(dft_woman)
+image_woman_translation = np.log(np.abs(shift_woman))
+
+shift_square = np.fft.fftshift(dft_square)
+image_square_translation = np.log(np.abs(shift_square))
+
+#展示图像
+plt.subplot(3,2,1)
+plt.imshow(image_woman, cmap='gray')
+plt.title('woman')
+plt.axis('off')
+
+plt.subplot(3,2,2)
+plt.imshow(image_square, cmap='gray')
+plt.title('square')
+plt.axis('off')
+
+plt.subplot(3,2,3)
+plt.imshow(image_woman_square, cmap='gray')
+plt.title('1.woman的幅频和square的相角')
+plt.axis('off')
+
+plt.subplot(3,2,4)
+plt.imshow(image_square_woman, cmap='gray')
+plt.title('2.square的幅频和woman的相角')
+plt.axis('off')
+
+plt.subplot(3,2,5)
+plt.imshow(image_woman_translation, cmap='gray')
+plt.title('3.将woman频谱幅度最亮处移到中心')
+plt.axis('off')
+
+plt.subplot(3,2,6)
+plt.imshow(image_square_translation, cmap='gray')
+plt.title('将square频谱幅度最亮处移到中心')
+plt.axis('off')
+
+plt.tight_layout()
+plt.show()