滤波算法(均值、中值、最大均值、最大中值、几何均值)

均值滤波

void meanfilter(Mat src, Mat dst, int kernalsize)
{
	int ksize;
	vector<uchar> tempdata;
	tempdata.clear();
	if (kernalsize % 2 == 0)
	{
		ksize = kernalsize / 2;
	}
	else
	{
		ksize = (kernalsize - 1) / 2;
	}
	if (kernalsize>src.rows || kernalsize>src.cols)
		cout << "核输入过大" << endl;

	for (int i = ksize; i < src.rows - ksize; i++)
	{
		uchar* datadst = dst.ptr<uchar>(i);
		for (int j = ksize; j < src.cols - ksize; j++)
		{
			
				for (int l = i - ksize; l <= i + ksize; l++)
				{
					uchar* datatemp = src.ptr<uchar>(l);
					for (int k = j - ksize; k <= j + ksize; k++)
					{
						tempdata.push_back(datatemp[k]);
					}
				}
				int tempsum = 0;
				for (size_t tempi = 0; tempi < tempdata.size(); tempi++)
				{
					tempsum += tempdata[tempi];
				}

				double s = 1.0 / (kernalsize*kernalsize);
				datadst[j] = s*tempsum;
				tempdata.clear();
		}
	}

	return;
}

修改：新方法解决了边界像素问题。而原始做法是将原图边界复制，即边界像素不做处理。

Mat mean(Mat src, int kernelSize)
{
	Mat dst = src.clone();
	int padding=0;
	if (kernelSize % 2 == 0)
	{
		padding = kernelSize / 2;
	}
	else
	{
		padding = (kernelSize - 1) / 2;
	}
	if (kernelSize>src.rows || kernelSize>src.cols)
		cout << "核输入过大" << endl;
	
	Mat addsrc(src.rows + padding, src.cols + padding, CV_8U);
	
	//将src边界放大，解决了边界像素的处理问题
	copyMakeBorder(src, addsrc, padding, padding, padding, padding, BORDER_CONSTANT, Scalar(255));

	for (int i = 0;