C++实现sobel算子

C++实现sobel算子,第1张

C++实现sobel算子

上一篇自动对焦里文章里用的评价函数,有用到opencv里的sobel算子。

我这边用C++实现下opencv里的这个算子

sobel算子的两个内核分别是{-1,0,1;-2,0,2;-1,0,1}   {-1,-2,-1;0,0,0;1,2,1}

先实现下opencv里图像彩色转灰色的算子

  

Mat BGR2GRAY(Mat img)
{
	int width = img.cols;
	int height = img.rows;
	Mat grayImg(height, width, CV_8UC1);
	
	uchar *p = grayImg.ptr(0);
	Vec3b *pImg = img.ptr(0);

	for (int i = 0; i < width*height; ++i)
	{
		p[i] = 0.2126*pImg[i][2] + 0.7152*pImg[i][1] + 0.0722*pImg[i][0];		
	}
	return grayImg;
}

然后实现下sobel算子

  

Mat sobel_filter(Mat img, bool horizontal)
{
	int height = img.rows;
	int width = img.cols;

	Mat out=Mat::zeros(height, width, CV_16S);

	double kernel[3][3] = { {-1,-2,-1},{0,0,0},{1,2,1} };	
	if (horizontal)
	{
		kernel[0][1] = 0;
		kernel[0][2] = 1;
		kernel[1][0] = -2;
		kernel[1][2] = 2;
		kernel[2][0] = -1;
		kernel[2][1] = 0;		
	}
	short* pOut = out.ptr(0);
	uchar *p1 = img.ptr(0);
	uchar *p2 = img.ptr(0);
	uchar *p3 = img.ptr(0);


	for (int j = 1; j < height-1; ++j)
	{
		pOut = pOut + width;
		p2 = p1 + width;
		p3 = p2 + width;				
		for (int i = 1; i < width-1; ++i)
		{
			pOut[i] = p1[i - 1] * kernel[0][0] + p1[i] * kernel[0][1] + p1[i + 1] * kernel[0][2] + p2[i - 1] * kernel[1][0]+p2[i + 1] * kernel[1][2] + p3[i - 1] * kernel[2][0] + p3[i] * kernel[2][1] + p3[i + 1] * kernel[2][2];
		}
		p1 = p1 + width;
	}
	return out;
}

OK

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原文地址: https://outofmemory.cn/zaji/5671137.html

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