cv2图像滤波_cv2拉普拉斯滤波函数-优快云博客

本文链接：https://blog.youkuaiyun.com/ZmgandXhf/article/details/128741306

这段代码展示了如何使用OpenCV库进行图像处理，包括均值滤波、高斯滤波、中值滤波、双边滤波、2D卷积、拉普拉斯滤波、2D卷积锐化、罗伯特滤波和索贝尔滤波，以实现图像平滑和边缘检测。

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# -*- coding:utf-8 -*-

import cv2
import numpy as np

path = r'./xxx.png'
img = cv2.imread(path)

# 均值滤波
img_blur = cv2.blur(img, (5, 5))
# cv2.imwrite(r"./均值滤波.png", img_blur)
cv2.imencode('.png', img_blur)[1].tofile('./均值滤波.png')
# 高斯滤波
img_GaussianBlur = cv2.GaussianBlur(img, (5, 5), 0, 0)
# cv2.imwrite(r"./高斯滤波.png", img_GaussianBlur)
cv2.imencode('.png', img_GaussianBlur)[1].tofile('./高斯滤波.png')
# 中值滤波
img_medianBlur = cv2.medianBlur(img, 5)
# cv2.imwrite(r"./中值滤波.png", img_medianBlur)
cv2.imencode('.png', img_medianBlur)[1].tofile('./中值滤波.png')
# 双边滤波
img_bilateralFilter = cv2.bilateralFilter(img, d=5, sigmaColor=100, sigmaSpace=100)
# cv2.imwrite(r"./双边滤波.png", img_bilateralFilter)
cv2.imencode('.png', img_bilateralFilter)[1].tofile('./双边滤波.png')
# 2D卷积滤波
kernel = np.ones((9, 9), np.float32) / 81
img_Filter2D = cv2.filter2D(img, -1, kernel)
cv2.imencode('.png', img_Filter2D)[1].tofile('./2D卷积滤波.png')
# 拉普拉斯滤波
img_Laplacian = cv2.Laplacian(img, cv2.CV_16S, ksize=3)
img_Laplacian = cv2.convertScaleAbs(img_Laplacian)
cv2.imencode('.png', img_Laplacian)[1].tofile('./拉普拉斯滤波.png')
# 2D卷积锐化
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
img_Sharpen1 = cv2.filter2D(img, -1, kernel_sharpen_1)
img_Sharpen2 = cv2.filter2D(img, -1, kernel_sharpen_2)
img_Sharpen3 = cv2.filter2D(img, -1, kernel_sharpen_3)
cv2.imencode('.png', img_Sharpen1)[1].tofile('./2D卷积锐化1.png')
cv2.imencode('.png', img_Sharpen2)[1].tofile('./2D卷积锐化2.png')
cv2.imencode('.png', img_Sharpen3)[1].tofile('./2D卷积锐化3.png')

# robert滤波
grayImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
kernelx = np.array([[-1, 0], [0, 1]], dtype=int)
kernely = np.array([[0, -1], [1, 0]], dtype=int)
x = cv2.filter2D(grayImage, cv2.CV_16S, kernelx)
y = cv2.filter2D(grayImage, cv2.CV_16S, kernely)
absX = cv2.convertScaleAbs(x)
absY = cv2.convertScaleAbs(y)
img_Robert = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
cv2.imencode('.png', img_Robert)[1].tofile('./Robert滤波.png')

# Sobel滤波
x = cv2.Sobel(img, cv2.CV_16S, 1, 0)
y = cv2.Sobel(img, cv2.CV_16S, 0, 1)
absx = cv2.convertScaleAbs(x)
absy = cv2.convertScaleAbs(y)
img_Sobel = cv2.addWeighted(absx, 0.5, absy, 0.5, 0)
cv2.imencode('.png', img_Sobel)[1].tofile('./Sobel滤波.png')