This page is about the 2D FFT, also called FFT2 in certain libraries and programming environments.
In [2]:
img = Image.open("/home/leo/kekw.jpg").convert('L') #img = img.resize((int(img.width / 4), int(img.height / 4)))
In [3]:
npimg = np.zeros((img.height, img.width)) for y in range(img.height): for x in range(img.width): npimg[y][x] = img.getpixel((x, y)) npimg = npimg / 256 img = npimg plt.imshow(img, cmap="gray") plt.colorbar()
Out [3]:
Out [3]:
Out:
In [4]:
def fft_rows(img): fft_img = np.zeros(img.shape, dtype=np.complex_) for y in range(img.shape[0]): row = [img[y][x] for x in range(img.shape[1])] row_fft = np.fft.fft(row) for x, col in enumerate(row_fft): fft_img[y][x] = col return fft_img img = fft_rows(img) plt.imshow(np.abs(img), vmax=1) plt.colorbar()
Out [4]:
Out [4]:
Out:
In [5]:
def fft_cols(img): fft_img = np.zeros(img.shape, dtype=np.complex_) for x in range(img.shape[1]): row = [img[y][x] for y in range(img.shape[0])] row_fft = np.fft.fft(row) for y, col in enumerate(row_fft): fft_img[y][x] = col return fft_img img = fft_cols(img) plt.imshow(np.abs(img), vmax=2) plt.colorbar()
Out [5]:
Out [5]:
Out:
In [6]:
plt.imshow(np.fft.ifft2(img).real, cmap="gray") plt.colorbar()
Out [6]:
Out [6]:
Out:
In [7]:
shp = img.shape img = img.flatten() decim = 50 for i, x in enumerate(img): img[i] = int(x.real / decim) * decim + int(x.imag / decim) * decim * 1j img = img.reshape(shp) plt.imshow(np.fft.ifft2(img).real, cmap="gray") plt.colorbar()
Out [7]:
Out [7]:
Out:
In [8]:
plt.imshow(np.abs(img), vmax=5) plt.colorbar()
Out [8]:
Out [8]:
Out:
In [9]:
np.max(img.real)/decim, np.min(img.real)/decim np.max(img.imag)/decim, np.min(img.imag)/decim #from collections import Counter #Counter(img.real.flatten()/decim) #Counter(img.imag.flatten()/decim)
Out [9]:
(4590.0, -1974.0)
Out [9]:
(645.0, -645.0)
