思维导图

1.线性滤波

//方框滤波操作
boxFilter( g_srcImage, g_dstImage1, -1,Size( g_nBoxFilterValue+1, g_nBoxFilterValue+1));

//均值滤波操作
blur( g_srcImage, g_dstImage2, Size( g_nMeanBlurValue+1, g_nMeanBlurValue+1), Point(-1,-1));

//高斯滤波操作
GaussianBlur( g_srcImage, g_dstImage3, Size( g_nGaussianBlurValue*2+1, g_nGaussianBlurValue*2+1 ), 0, 0);

2.非线性滤波

//中值滤波操作的回调函数
medianBlur ( g_srcImage, g_dstImage4, g_nMedianBlurValue*2+1 );

//双边滤波操作的回调函数
bilateralFilter ( g_srcImage, g_dstImage5, g_nBilateralFilterValue, g_nBilateralFilterValue*2, g_nBilateralFilterValue/2 );

3.形态学滤波

//开运算/闭运算
morphologyEx(g_srcImage, g_dstImage, MORPH_OPEN, element);
morphologyEx(g_srcImage, g_dstImage, MORPH_CLOSE, element);

//腐蚀/膨胀
erode(g_srcImage, g_dstImage, element);
dilate(g_srcImage, g_dstImage, element);

//顶帽运算/黑帽运算
morphologyEx(g_srcImage, g_dstImage, MORPH_TOPHAT , element);
morphologyEx(g_srcImage, g_dstImage, MORPH_BLACKHAT, element);

4.漫水填充

threshold(g_maskImage, g_maskImage, 1, 128, THRESH_BINARY);
		area = floodFill(dst, g_maskImage, seed, newVal, &ccomp, Scalar(LowDifference, LowDifference, LowDifference),
			Scalar(UpDifference, UpDifference, UpDifference), flags);

5.尺寸缩放

//向上采样
pyrUp( g_tmpImage, g_dstImage, Size( g_tmpImage.cols*2, g_tmpImage.rows*2 ) );

//向下采样
pyrDown( g_tmpImage, g_dstImage, Size( g_tmpImage.cols/2, g_tmpImage.rows/2 ));

//尺寸调整
resize(g_tmpImage,g_dstImage,Size( g_tmpImage.cols/2, g_tmpImage.rows/2 ));

6.阈值化

//调用阈值函数
threshold(g_grayImage,g_dstImage,g_nThresholdValue,255,g_nThresholdType);

参考书籍《OpenCV3编程入门》