eda.py 文件源码

def plot_wavelet_decomposition(image, level=3):
    """
    Plot of 2D wavelet decompositions for given number of levels.

    image needs to be either a colour channel or greyscale image:
        rgb: self.I[:, :, n], where n = {0, 1, 2}
        greyscale: use rgb_to_grey(self.I)

    """
    coeffs = pywt.wavedec2(image, wavelet='haar', level=level)
    for i, (cH, cV, cD) in enumerate(coeffs[1:]):
        if i == 0:
            cAcH = np.concatenate((coeffs[0], cH), axis=1)
            cVcD = np.concatenate((cV, cD), axis=1)
            plot_image = np.concatenate((cAcH, cVcD), axis=0)
        else:
            plot_image = np.concatenate((plot_image, cH), axis=1)
            cVcD = np.concatenate((cV, cD), axis=1)
            plot_image = np.concatenate((plot_image, cVcD), axis=0)

    plt.grid(False)
    io.imshow(abs(plot_image), cmap='gray_r')
    plt.show()