Stdfilt in Opencv

I am c开发者_Python百科urrently looking through he documentation of openCV atempting to find the matlab equivelent of stdfilt could anyone point me in the correct direction?

thanks.

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Looking at the source code inside the stdfilt.m file, we can see it is implemented using convolution..

I ported the code to Python, it should be straightforward to rewrite in C\C++:

import cv2
import numpy as np

img = cv2.imread('fruits.jpg', True)
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
img = img / 255.0

# c = imfilter(I,h,'symmetric');
h = np.ones((3,3))
n = h.sum()
n1 = n - 1
c1 = cv2.filter2D(img**2, -1, h/n1, borderType=cv2.BORDER_REFLECT)
c2 = cv2.filter2D(img, -1, h, borderType=cv2.BORDER_REFLECT)**2 / (n*n1)
J = np.sqrt( np.maximum(c1-c2,0) )

cv2.imshow('stdfilt', J)
cv2.waitKey(0)
cv2.destroyWindow('stdfilt')

The result:

Compare against MATLAB's version:

I = imread('fruits.jpg');
I = im2double(rgb2gray(I));
imshow(stdfilt(I))

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I think you're out of luck - there's a function for mean and std dev of an entire image, cvAvgSdv, but nothing for local std dev as far as I can see. Still, it shouldn't be too hard to write one.

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template<class T>
cv::Mat     POW2(const cv::Mat& a)
{
    cv::Mat t(a.size(),a.type(),cv::Scalar(0));
    for (int j=0; j<a.rows; j++) {
        const T* ap=a.ptr<T>(j);
        T* tp=t.ptr<T>(j);
        for (int i=0; i<a.cols; i++)    tp[i]=ap[i]*ap[i];
    }
    return t;
}

template<class T>
cv::Mat     SQRT(const cv::Mat& a)
{
    cv::Mat t(a.size(),a.type(),cv::Scalar(0));
    for (int j=0; j<a.rows; j++) {
        const T* ap=a.ptr<T>(j);
        T* tp=t.ptr<T>(j);
        for (int i=0; i<a.cols; i++)    tp[i]=sqrt(ap[i]);
    }
    return t;
}

Mat stdfilt(Mat_<float> const& I, InputArray kernel, int borderType)
{
    Mat G1,G2;
    Mat I2=POW2<float>(I);
    Scalar n=sum(kernel);
    filter2D( I2, G2, CV_32F,kernel, Point(-1,-1),0,borderType);
    G2=G2/(n[0]-1.);
    filter2D( I,  G1, CV_32F,kernel, Point(-1,-1),0,borderType);
    G1=POW2<float>(G1)/(n[0]*(n[0]-1.));
    return SQRT<float>(MAXM<float>(G2-G1,0.));
}


Mat stdfilt(Mat_<float> const& image32f, int ksize, int borderType)
{
    int kernel_size = 1 + 2*ksize;
    Mat kernel = Mat::ones( kernel_size, kernel_size, CV_32F );
    return stdfilt(image32f, kernel, borderType);
}