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以下是用LUT实现的直方图均衡算法函数，请填空完成/输入参数：unsigned char img8位灰度图像位图数据首地址int count图像像素个数输出参数：unsigned char img8位灰度图像位图数据首地址功能：8位灰度图像的直方图均衡化/void Equalize(unsigned char img,int count){int i;unsigned char p = img;//统计直方图int hist[256];memset(hist,0,256sizeof(int));for(i = 0; i < count; i++){hist[p++]++;}//计算映射关系unsigned char LUT[256];int H = 0;for(i = 0; i < 256;i++){H += _____;LUT[i] = 255 * H / _;}//逐点替换for(i = 0; i < count; i++){*img = LUT[___];img++;}}

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以下是用LUT实现的自动对比度调整算法，请填空完成。/输入参数：unsigned char img8位灰度图像位图数据首地址int count图像像素个数输出参数：unsigned char img8位灰度图像位图数据首地址功能：8位灰度图像的自动对比度增强/void AutoContrast(unsigned char img,int count){//求取图像中的最小像素值和最大像素值int grayLow = 255, grayHigh = 0;int i;unsigned char p = img;for(i = 0; i < count; i++){if(p < grayLow) grayLow = p;if(p > grayHigh) grayHigh = p;p++;}if(grayHigh - grayLow == 0)return;//图像中的灰度值均相等，无法进行自动对比度调整unsigned char LUT[256];for(i = 0; i < 256;i++){LUT[i] = (i - _) 255/ ( grayHigh - grayLow );}//自动对比度映射p = img;for(i = 0; i < count; i++){p++ =____;}}

以下是二维高斯滤波器的xy分离实现形式。请填空。输入参数：const unsigned char src_data输入的8位灰度图像位图数据首地址int cols 像素列数int rows 像素行数double sigma 标准差输出参数：unsigned char dst_data高斯滤波后的8位灰度图像位图数据首地址功能：8位灰度图像的二维高斯滤波/void GaussianFilter(const unsigned char src_data, unsigned char dst_data,int cols,int rows,double sigma){int i,j,m,n;float sum=0;int center = (int)(3 * sigma);//3sigma原理int length = ____________;float* kernel = new float[length];double sigma2 = sigma*sigma;//由高斯公式计算滤波系数for(i = 0;i

图像几何变换一般包括两个步骤：空间变换和____________________

以下程序用OpenCV读入一幅彩色图像并显示。#include #include #include using namespace cv;using namespace std;int main( int argc, char** argv ){ image;image = (argv[1], CV_LOAD_IMAGE_COLOR);namedWindow( "Display window",CV_WINDOW_AUTOSIZE );_____________( "Display window", image );waitKey(0);return 0;}