95 lines
2.7 KiB
Python
95 lines
2.7 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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img1 = plt.imread("wmi1.jpg")/float(2**8)
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img2 = plt.imread("wmi2.jpg")/float(2**8)
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img3 = plt.imread("wmi3.jpg")/float(2**8)
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#plt.imshow(img)
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#plt.show()
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def zad2(img, _diamiter, n):
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shape = img.shape[:2]
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def draw_cicle(shape,diamiter):
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assert len(shape) == 2
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TF = np.zeros(shape,dtype=np.bool)
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center = np.array(TF.shape)/2.0
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for iy in range(shape[0]):
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for ix in range(shape[1]):
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TF[iy,ix] = (iy- center[0])**2 + (ix - center[1])**2 < diamiter **2
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return(TF)
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TFcircleIN = draw_cicle(shape=img.shape[:2],diamiter=_diamiter)
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TFcircleOUT = ~TFcircleIN
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fft_img = np.zeros_like(img,dtype=complex)
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for ichannel in range(fft_img.shape[2]):
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fft_img[:,:,ichannel] = np.fft.fftshift(np.fft.fft2(img[:,:,ichannel]))
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def filter_circle(TFcircleIN,fft_img_channel):
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temp = np.zeros(fft_img_channel.shape[:2],dtype=complex)
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temp[TFcircleIN] = fft_img_channel[TFcircleIN]
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return(temp)
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fft_img_filtered_IN = []
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fft_img_filtered_OUT = []
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## for each channel, pass filter
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for ichannel in range(fft_img.shape[2]):
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fft_img_channel = fft_img[:,:,ichannel]
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## circle IN
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temp = filter_circle(TFcircleIN,fft_img_channel)
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fft_img_filtered_IN.append(temp)
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## circle OUT
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temp = filter_circle(TFcircleOUT,fft_img_channel)
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fft_img_filtered_OUT.append(temp)
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fft_img_filtered_IN = np.array(fft_img_filtered_IN)
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fft_img_filtered_IN = np.transpose(fft_img_filtered_IN,(1,2,0))
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fft_img_filtered_OUT = np.array(fft_img_filtered_OUT)
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fft_img_filtered_OUT = np.transpose(fft_img_filtered_OUT,(1,2,0))
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def inv_FFT_all_channel(fft_img):
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img_reco = []
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for ichannel in range(fft_img.shape[2]):
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img_reco.append(np.fft.ifft2(np.fft.ifftshift(fft_img[:,:,ichannel])))
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img_reco = np.array(img_reco)
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img_reco = np.transpose(img_reco,(1,2,0))
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return(img_reco)
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img_reco = inv_FFT_all_channel(fft_img)
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img_reco_filtered_IN = inv_FFT_all_channel(fft_img_filtered_IN)
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img_reco_filtered_OUT = inv_FFT_all_channel(fft_img_filtered_OUT)
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fig = plt.figure(figsize=(25,18))
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ax = fig.add_subplot(1,3,1)
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ax.imshow(np.abs(img_reco))
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ax.set_title("original image")
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ax = fig.add_subplot(1,3,2)
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ax.imshow(np.abs(img_reco_filtered_IN))
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ax.set_title("low pass filter image")
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ax = fig.add_subplot(1,3,3)
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ax.imshow(np.abs(img_reco_filtered_OUT))
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ax.set_title("high pass filtered image")
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plt.savefig(f"zdjęcie{n}.jpg")
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#plt.show()
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zad2(img1, 150, 1)
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zad2(img2, 120, 2)
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zad2(img3, 150, 3)
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