【二值化】sauvola算法实现

实现了sauvola算法，原论文去google一下就有了~

参数是：k, windowSize，自己调调看效果

void sauvola(unsigned char * grayImage,unsigned char * biImage,int w,int h,int k,int windowSize)
{	
	int whalf = windowSize >> 1;
	
	int i,j;
	int IMAGE_WIDTH = w;
	int IMAGE_HEIGHT = h;
	// create the integral image
	unsigned long * integralImg = (unsigned long*)malloc(IMAGE_WIDTH*IMAGE_HEIGHT*sizeof(unsigned long*));
	unsigned long * integralImgSqrt = (unsigned long*)malloc(IMAGE_WIDTH*IMAGE_HEIGHT*sizeof(unsigned long*));
	int sum = 0;
	int sqrtsum = 0;
	int index;
	for (i=0; i<IMAGE_HEIGHT; i++)
	{
		// reset this column sum
		sum = 0;
		sqrtsum = 0;

		for (j=0; j<IMAGE_WIDTH; j++)
		{
			index = i*IMAGE_WIDTH+j;

			sum += grayImage[index];
			sqrtsum += grayImage[index] * grayImage[index];

			if (i==0)
			{
				integralImg[index] = sum;
				integralImgSqrt[index] = sqrtsum;
			}
			else
			{
				integralImgSqrt[index] = integralImgSqrt[(i-1)*IMAGE_WIDTH+j] + sqrtsum;
				integralImg[index] = integralImg[(i-1)*IMAGE_WIDTH+j] + sum;
			}
		}
	}
	
	//Calculate the mean and standard deviation using the integral image
	int xmin,ymin,xmax,ymax;
	double mean,std,threshold;
	double diagsum,idiagsum,diff,sqdiagsum,sqidiagsum,sqdiff,area;

	for (i=0; i<IMAGE_WIDTH; i++){
		for (j=0; j<IMAGE_HEIGHT; j++){
			xmin = max(0,i - whalf);
			ymin = max(0,j - whalf);
			xmax = min(IMAGE_WIDTH-1,i+whalf);
			ymax = min(IMAGE_HEIGHT-1,j+whalf);
			
			area = (xmax - xmin + 1) * (ymax - ymin + 1);
			if(area <= 0)
			{
				biImage[i * IMAGE_WIDTH + j] = 255;
				continue;
			}
			
			if(xmin == 0 && ymin == 0){
				diff = integralImg[ymax * IMAGE_WIDTH + xmax];
				sqdiff = integralImgSqrt[ymax * IMAGE_WIDTH + xmax];
			}else if(xmin > 0 && ymin == 0){
				diff = integralImg[ymax * IMAGE_WIDTH + xmax] - integralImg[ymax * IMAGE_WIDTH + xmin - 1];
				sqdiff = integralImgSqrt[ymax * IMAGE_WIDTH + xmax] - integralImgSqrt[ymax * IMAGE_WIDTH + xmin - 1];	
			}else if(xmin == 0 && ymin > 0){
				diff = integralImg[ymax * IMAGE_WIDTH + xmax] - integralImg[(ymin - 1) * IMAGE_WIDTH + xmax];
				sqdiff = integralImgSqrt[ymax * IMAGE_WIDTH + xmax] - integralImgSqrt[(ymin - 1) * IMAGE_WIDTH + xmax];;
			}else{
				diagsum = integralImg[ymax * IMAGE_WIDTH + xmax] + integralImg[(ymin - 1) * IMAGE_WIDTH + xmin - 1];
				idiagsum = integralImg[(ymin - 1) * IMAGE_WIDTH + xmax] + integralImg[ymax * IMAGE_WIDTH + xmin - 1];
				diff = diagsum - idiagsum;

				sqdiagsum = integralImgSqrt[ymax * IMAGE_WIDTH + xmax] + integralImgSqrt[(ymin - 1) * IMAGE_WIDTH + xmin - 1];
				sqidiagsum = integralImgSqrt[(ymin - 1) * IMAGE_WIDTH + xmax] + integralImgSqrt[ymax * IMAGE_WIDTH + xmin - 1];
				sqdiff = sqdiagsum - sqidiagsum;
			}

			mean = diff/area;
			std  = sqrt((sqdiff - diff*diff/area)/(area-1));
			threshold = mean*(1+k*((std/128)-1));
			if(grayImage[j*IMAGE_WIDTH + i] < threshold)
				biImage[j*IMAGE_WIDTH + i] = 0;
			else
				biImage[j*IMAGE_WIDTH + i] = 255;	
		}
	}
	
	free(integralImg);
	free(integralImgSqrt);
}