image.py 文件源码

def visualize_derivatives(image):
    '''
    Plot gradient on left and Laplacian on right.
    Only tested on 2D 1-channel float imags
    '''
    dx1,dy1 = np.gradient(image)
    gradient = dx1 + 1j*dy1
    a1 = np.abs(gradient)
    plt.figure(None,(12,6))
    plt.subplot(121)
    a1 = mean_center(blur(exposure.equalize_hist(unitize(a1)),1))
    plt.imshow(a1,
        origin='lower',interpolation='nearest',cmap='gray',extent=(0,64,)*2)
    plt.title('Gradient Magnitude')
    plt.subplot(122)
    laplacian = scipy.ndimage.filters.laplace(image)
    lhist = mean_center(
        blur(exposure.equalize_hist(unitize(laplacian)),1))
    plt.imshow(lhist,
        origin='lower',interpolation='nearest',cmap='gray',extent=(0,64,)*2)
    plt.title('Laplacian')
    return gradient, laplacian