自定义卷积核，如3×3、5×5、7×7、9×9、11×11
Tip：卷积核需归一化。
# -*- coding: utf-8 -*-
"""
Created on Sat Aug 25 14:35:33 2018
@author: Miracle
"""
import cv2
import numpy as np
#加载图像
image = cv2.imread('../data/lena.jpg')
#自定义卷积核
kernel_sharpen_1 = np.array([
[-1,-1,-1],
[-1,9,-1],
[-1,-1,-1]])
kernel_sharpen_2 = np.array([
[1,1,1],
[1,-7,1],
[1,1,1]])
kernel_sharpen_3 = np.array([
[-1,-1,-1,-1,-1],
[-1,2,2,2,-1],
[-1,2,8,2,-1],
[-1,2,2,2,-1],
[-1,-1,-1,-1,-1]])/8.0
#卷积
output_1 = cv2.filter2D(image,-1,kernel_sharpen_1)
output_2 = cv2.filter2D(image,-1,kernel_sharpen_2)
output_3 = cv2.filter2D(image,-1,kernel_sharpen_3)
#显示锐化效果
cv2.imshow('Original Image',image)
cv2.imshow('sharpen_1 Image',output_1)
cv2.imshow('sharpen_2 Image',output_2)
cv2.imshow('sharpen_3 Image',output_3)
#停顿
if cv2.waitKey(0) & 0xFF == 27:
cv2.destroyAllWindows()
