94 lines
2.7 KiB
Python
94 lines
2.7 KiB
Python
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import numpy as np
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import matplotlib.pyplot as plt
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from numpy.fft import fft2, ifft2, fftshift, ifftshift
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from PIL import Image
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from datetime import datetime
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def modify_b_channel_frequency(image, modify_pos, factor):
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# 提取B通道并进行FFT
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b_channel = image[:, :, 2]
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f_b = fftshift(fft2(b_channel))
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# 图像尺寸
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N, M = b_channel.shape
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amplitude = np.abs(f_b)
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phase = np.angle(f_b)
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# 获取修改位置的原始幅度
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x, y = modify_pos
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original_amplitude = np.abs(f_b[x, y])
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# 修改指定位置的频率幅度
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amplitude[x,y] = original_amplitude * factor
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modified_amplitude = amplitude[x, y]
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amplitude[N-x, M-y] = amplitude[N-x, M-y] * factor
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# modified_amplitude = original_amplitude
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f_b = amplitude * np.exp(1j * phase)
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# 执行逆FFT转换回空间域
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modified_b_channel = ifft2(ifftshift(f_b))
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modified_b_channel = np.real(modified_b_channel)
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# 保证修改后的B通道在合法范围内
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# modified_b_channel = np.clip(modified_b_channel, 0, 255).astype(np.uint8)
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# 合并修改后的B通道回原图
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# image[:, :, 2] = modified_b_channel
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# 返回修改前后的幅度信息
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return image, original_amplitude, modified_amplitude, modified_b_channel
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def check_modification_effect(image, modify_pos):
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# 再次进行FFT以检查修改效果
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# b_channel = image[:, :, 2]
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b_channel = image
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f_b = fftshift(fft2(b_channel))
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x, y = modify_pos
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current_amplitude = np.abs(f_b[x, y])
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return current_amplitude, f_b
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# 加载图像
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img_path = 'demo_border.png'
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image = np.array(Image.open(img_path))
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# 设置修改位置和放大因子
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modify_pos = (110, 125) # 修改位置
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factor = 2 # 放大原有的幅度
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# 修改B通道并检查效果
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modified_image, original_amplitude, modified_amplitude, modified_b_channel = modify_b_channel_frequency(image, modify_pos, factor)
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image[:, :, 2] = modified_b_channel
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filename = f"{datetime.now().strftime('%Y%m%d%H%M%S')}.png"
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Image.fromarray(image).save(filename)
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# final_image = Image.fromarray(image)
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# final_image.save(filename)
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#
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img = Image.open(filename)
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img = np.array(img)
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b_channel = img[:, :, 2]
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current_amplitude, f_b = check_modification_effect(modified_b_channel, modify_pos)
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# 输出幅度对比
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print(f"Original Amplitude: {original_amplitude}")
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print(f"Modified Amplitude (should be): {modified_amplitude}")
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print(f"Current Amplitude (after modifications and IFFT): {current_amplitude}")
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# 打印出f_b中最大幅度
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# print(f"Maximum Amplitude in f_b: {np.max(np.abs(f_b))}")
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# 可视化显示
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plt.figure(figsize=(12, 6))
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plt.subplot(121)
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plt.imshow(image)
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plt.title('Original Image')
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plt.subplot(122)
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plt.imshow(modified_image)
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plt.title('Modified Image')
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plt.show()
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