Opencv 旋转Gabor滤波器

在这里分别取A=0,45,90,135来求得旋转Gabor滤波器。其它参数和上节Gabor滤波器一样，K=111，\sigma=10，\gamma = 1.2，\lambda =10，p=0。

Gabor滤波器可以通过这里的方法简单实现。

输入 (imori.jpg)	输出

python实现：

import cv2
import numpy as np
import matplotlib.pyplot as plt


# Gabor
def Gabor_filter(K_size=111, Sigma=10, Gamma=1.2, Lambda=10, Psi=0, angle=0):
    # get half size
    d = K_size // 2

    # prepare kernel
    gabor = np.zeros((K_size, K_size), dtype=np.float32)

    # each value
    for y in range(K_size):
        for x in range(K_size):
            # distance from center
            px = x - d
            py = y - d

            # degree -> radian
            theta = angle / 180. * np.pi

            # get kernel x
            _x = np.cos(theta) * px + np.sin(theta) * py

            # get kernel y
            _y = -np.sin(theta) * px + np.cos(theta) * py

            # fill kernel
            gabor[y, x] = np.exp(-(_x**2 + Gamma**2 * _y**2) / (2 * Sigma**2)) * np.cos(2*np.pi*_x/Lambda + Psi)

    # kernel normalization
    gabor /= np.sum(np.abs(gabor))

    return gabor


# define each angle
As = [0, 45, 90, 135]

# prepare pyplot
plt.subplots_adjust(left=0, right=1, top=1, bottom=0, hspace=0, wspace=0.2)

# each angle
for i, A in enumerate(As):
    # get gabor kernel
    gabor = Gabor_filter(K_size=111, Sigma=10, Gamma=1.2, Lambda=10, Psi=0, angle=A)

    # normalize to [0, 255]
    out = gabor - np.min(gabor)
    out /= np.max(out)
    out *= 255

    out = out.astype(np.uint8)
    plt.subplot(1, 4, i+1)
    plt.imshow(out, cmap='gray')
    plt.axis('off')
    plt.title("Angle "+str(A))

plt.savefig("out.png")
plt.show()