数学之路-python计算实战(19)-机器视觉-卷积滤波

filter2D

Convolves an image with the kernel.

C++: void filter2D(InputArray src, OutputArray dst, int ddepth, InputArraykernel, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT )

Python: cv2.filter2D(src, ddepth, kernel[, dst[, anchor[, delta[, borderType]]]]) → dst

C: void cvFilter2D(const CvArr* src, CvArr* dst, const CvMat* kernel, CvPointanchor=cvPoint(-1,-1) )

Python: cv.Filter2D(src, dst, kernel, anchor=(-1, -1)) → None

Parameters:

src – input image. dst – output image of the same size and the same number of channels as src. ddepth – desired depth of the destination image; if it is negative, it will be the same as src.depth(); the following combinations ofsrc.depth() and ddepth are supported: src.depth() = CV_8U, ddepth = -1/CV_16S/CV_32F/CV_64F src.depth() = CV_16U/CV_16S, ddepth = -1/CV_32F/CV_64F src.depth() = CV_32F, ddepth = -1/CV_32F/CV_64F src.depth() = CV_64F, ddepth = -1/CV_64F when ddepth=-1, the output image will have the same depth as the source. kernel – convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split() and process them individually. anchor – anchor of the kernel that indicates the relative position of a filtered point within the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor is at the kernel center. delta – optional value added to the filtered pixels before storing them in dst. borderType – pixel extrapolation method (seeborderInterpolate() for details).

The function applies an arbitrary linear filter to an image. In-place operation is supported. When the aperture is partially outside the image, the function interpolates outlier pixel values according to the specified border mode.

# -*- coding: utf-8 -*-
#卷积滤波
#code:[email protected]
import cv2
import numpy as np
fn="test2.jpg"
myimg=cv2.imread(fn)
img=cv2.cvtColor(myimg,cv2.COLOR_BGR2GRAY)
myh=np.array([[0,1,0],[1,-4,1],[0,1,0]])
jgimg=cv2.filter2D(img,-1,myh)
cv2.imshow(‘src‘,img)
cv2.imshow(‘dst‘,jgimg)
cv2.waitKey()
cv2.destroyAllWindows()

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