Gaussian Filter algorithm

gaussian_filter.py

Hg = np.zeros((20,20))
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
for i in range(20):
    for j in range(20):
        Hg[i,j] = np.exp(-((i-10) ** 2 + (j-10)**2)/10)
        
gaussian_blur = scipy.signal.convolve2d(gray, Hg, mode='same')
gray_high = gray - gaussian_blur
gray_enhanced = gray + 0.025 * gray_high

imgs = np.array([ gray, gaussian_blur, gray_high, gray_enhanced])
labels = ['Original', 'Filtered', 'High Components', 'Enhanced']
for i in range(1, column*row+1):

    ax = fig.add_subplot(row,column,i)
    ax.set_title(labels[i-1])
    plt.imshow(imgs[i-1], cmap='gray')
plt.show()