图像保边滤波算法集锦--局部均值滤波算法与实现

局部均值滤波算法是基于均值改进的一种具有一定保边能力的滤波器，参考论文为Lee filter Digital image enhancement and noise filtering by using local statistics，具体算法如下：

本人C实现效果如下：

主要代码如下：

//导向滤波
int GuidedFilter(unsigned char* srcData, int width ,int height, int radius, float delta)
{
	float *data = (float*)malloc(sizeof(float) * width * height);
	float *meanIP = (float*)malloc(sizeof(float) * width * height);
	float *corrIP = (float*)malloc(sizeof(float) * width * height);
	float *varIP = (float*)malloc(sizeof(float) * width * height);
	float *a = (float*)malloc(sizeof(float) * width * height);
	float *b = (float*)malloc(sizeof(float) * width * height);
	for(int i = 0; i < width * height; i++)
	{
		data[i] = (float)srcData[i] / 255.0;
	}
	//mean and cov compute
	MeanCovMapCalculate(data, width, height, meanIP, radius);
	for(int i = 0; i < width * height; i++)
	{
		data[i] *= data[i];
	}
	//mean and cov compute
	MeanCovMapCalculate(data, width, height, corrIP, radius);
	for(int i = 0; i < width * height; i++)
	{
		varIP[i] = corrIP[i] - meanIP[i] * meanIP[i];
	}
	for(int i = 0; i < width * height; i++)
	{
		a[i] = varIP[i] / (varIP[i] + delta);
		b[i] = meanIP[i] - a[i] * meanIP[i];
	}
	//mean and cov compute
    MeanCovMapCalculate(a, width, height, meanIP, radius);
	MeanCovMapCalculate(b, width, height, corrIP, radius);
	for(int i = 0; i < width * height; i++)
	{
		srcData[i] = (unsigned char)(CLIP3((meanIP[i] * srcData[i]/255.0f + corrIP[i])*255.0f, 0, 255));
	}
	free(data);
	free(meanIP);
	free(corrIP);
	free(varIP);
	free(a);
	free(b);
	return 0;
};
//4通道处理
void f_GuidedFilter(unsigned char* srcData, int nWidth, int nHeight, int nStride, int radius, float delta)
{
	if (srcData == NULL)
	{
		return;
	}
	unsigned char* rData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* gData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* bData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* pSrc = srcData;
	int Y, CB, CR;
	unsigned char* pR = rData;
	unsigned char* pG = gData;
	unsigned char* pB = bData;
	for(int j = 0; j < nHeight; j++)
	{
		for(int i = 0; i < nWidth; i++)
		{
			*pR = pSrc[2];
			*pG = pSrc[1];
			*pB = pSrc[0];
			pR++;
			pG++;
			pB++;
			pSrc += 4;
		}
	}
	//并行处理
	#pragma omp parallel sections  num_threads(omp_get_num_procs())
	{
		#pragma omp  section					
			GuidedFilter(rData, nWidth, nHeight, radius, delta);
		#pragma omp  section
			GuidedFilter(gData, nWidth, nHeight, radius, delta);
		#pragma omp  section
			GuidedFilter(bData, nWidth, nHeight, radius, delta);
	}
	pSrc = srcData;
	pR = rData;
	pG = gData;
	pB = bData;
	int R, G, B;
	for(int j = 0; j < nHeight; j++)
	{
		for(int i = 0; i < nWidth; i++)
		{
            pSrc[0] = *pB;
			pSrc[1] = *pG;
			pSrc[2] = *pR;
			pR++;
			pG++;
			pB++;
			pSrc += 4;
		}
	}
	free(rData);
	free(gData);
	free(bData);
}
//单通道处理
void f_GuidedFilterOneChannel(unsigned char* srcData, int nWidth, int nHeight, int nStride, int radius, float delta)
{
	if (srcData == NULL)
	{
		return;
	}
	unsigned char* yData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* cbData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* crData = (unsigned char*)malloc(sizeof(unsigned char) * nWidth * nHeight);
	unsigned char* pSrc = srcData;
	int Y, CB, CR;
	unsigned char* pY = yData;
	unsigned char* pCb = cbData;
	unsigned char* pCr = crData;
	for(int j = 0; j < nHeight; j++)
	{
		for(int i = 0; i < nWidth; i++)
		{
			RGBToYCbCr(pSrc[2],pSrc[1],pSrc[0],&Y,&CB,&CR);
			*pY = Y;
			*pCb = CB;
			*pCr = CR;
			pY++;
			pCb++;
			pCr++;
			pSrc += 4;
		}
	}
	GuidedFilter(yData, nWidth, nHeight, radius, delta);
	pSrc = srcData;
	pY = yData;
	pCb = cbData;
	pCr = crData;
	int R, G, B;
	for(int j = 0; j < nHeight; j++)
	{
		for(int i = 0; i < nWidth; i++)
		{
			YCbCrToRGB(*pY, *pCb, *pCr, &R, &G, &B);
            pSrc[0] = B;
			pSrc[1] = G;
			pSrc[2] = R;
			pY++;
			pCb++;
			pCr++;
			pSrc += 4;
		}
	}
}

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