改变图片强调可修改r,如s.val[i]*scale*r
2024-06-05 05:17:03
/************中心环形矢量场*马鞍矢量场*****卷积白噪声纹理***********/#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <malloc.h>
#include <cv.h>
#include <highgui.h>
#include <iostream>
#include <fstream>
#include "netcdfcpp.h"
using namespace std;#define SQUARE_FLOW_FIELD_SZ 400
#define DISCRETE_FILTER_SIZE 2048 //离散的滤波尺寸
#define LOWPASS_FILTR_LENGTH 10.00000f //低通滤波长度
#define LINE_SQUARE_CLIP_MAX 100000.0f //线性平方夹
#define VECTOR_COMPONENT_MIN 0.050000f //矢量分量最小值void SyntheszSaddle(int n_xres, int n_yres, float* pVectr);
void NormalizVectrs(int n_xres, int n_yres, float* pVectr,float* vecSize);
void GenBoxFiltrLUT(int LUTsiz, float* p_LUT0, float* p_LUT1);
void MakeWhiteNoise(int n_xres, int n_yres, float* pNoise);
void FlowImagingLIC(int n_xres, int n_yres, float* pVectr, float* pNoise, float* pImage, float* p_LUT0, float* p_LUT1, float krnlen);
void WriteImage2PPM(int n_xres, int n_yres, float* pImage,char* f_name);
void color(int n_xres, int n_yres,float *pImage,float* vecSize);double maxvecmag;void main()
{int n_xres = 721;int n_yres = 281;// int n_xres = 1441;
// int n_yres = 561;// int n_xres = 2881;
// int n_yres = 1121;
//
// int n_xres = 5761;
// int n_yres = 2241;// int n_xres = 11521;
// int n_yres = 2241;float* pVectr = (float* ) malloc( sizeof(float ) * n_xres * n_yres * 2 );float* p_LUT0 = (float* ) malloc( sizeof(float ) * DISCRETE_FILTER_SIZE);float* p_LUT1 = (float* ) malloc( sizeof(float ) * DISCRETE_FILTER_SIZE);float* pNoise = (float* ) malloc( sizeof(float) * n_xres * n_yres );float* pImage = (float* ) malloc( sizeof(float) * n_xres * n_yres );float* vecSize = (float* ) malloc( sizeof(float) * n_xres*n_yres );SyntheszSaddle( n_xres, n_yres, pVectr);//CenterFiled(n_xres, n_yres, pVectr);//包含矢量归一化NormalizVectrs(n_xres, n_yres, pVectr,vecSize);//所以这就不用矢量归一化了，因为之前的马鞍矢量场生成函数里没有归一化，才有此步的MakeWhiteNoise(n_xres, n_yres, pNoise);GenBoxFiltrLUT(DISCRETE_FILTER_SIZE, p_LUT0, p_LUT1);FlowImagingLIC(n_xres, n_yres, pVectr, pNoise, pImage, p_LUT0, p_LUT1, LOWPASS_FILTR_LENGTH);color(n_xres, n_yres,pImage,vecSize);//WriteImage2PPM(n_xres, n_yres, pImage, "LIC.ppm");
// WriteImage2PPM(n_xres, n_yres, pImage, "LIC_721_281.ppm");
// WriteImage2PPM(n_xres, n_yres, pImage, "LIC1441_561.ppm");
// WriteImage2PPM(n_xres, n_yres, pImage, "LIC2281_1121.ppm");//WriteImage2PPM(n_xres, n_yres, pImage, "LIC5761_1121.ppm");//WriteImage2PPM(n_xres, n_yres, pImage, "LIC_11521_2241.ppm");//system("pause");free(pVectr); pVectr = NULL;free(p_LUT0); p_LUT0 = NULL;free(p_LUT1); p_LUT1 = NULL;free(pNoise); pNoise = NULL;free(pImage); pImage = NULL;
}/// 中心环形矢量场图形 synthesize a saddle-shaped vector field ///
void SyntheszSaddle(int n_xres, int n_yres, float* pVectr)
{ static const int LatNum = n_yres;static const int LonNum = n_xres;static const int Time = 1;static const int TMP = Time*LonNum*LatNum;NcFile dataReadFile("global_721_281.nc",NcFile::ReadOnly);
// NcFile dataReadFile("global_1441_561.nc",NcFile::ReadOnly);
// NcFile dataReadFile("global_2881_1121.nc",NcFile::ReadOnly);// NcFile dataReadFile("global_5761_2241.nc",NcFile::ReadOnly);//NcFile dataReadFile("global_11521_2241.nc",NcFile::ReadOnly);if (!dataReadFile.is_valid()){std::cout<<"couldn't open file!"<<std::endl;}double *Tmp_UX = new double[TMP];double *Tmp_VY = new double[TMP];double *Tmp_LAT = new double[TMP];double *Tmp_LON = new double[TMP];NcVar *dataTmp_LAT = dataReadFile.get_var("LAT"); NcVar *dataTmp_LON = dataReadFile.get_var("LONN359_361"); NcVar *dataTmp_UX = dataReadFile.get_var("UX"); NcVar *dataTmp_VY = dataReadFile.get_var("VY"); dataTmp_LAT->get(Tmp_LAT,LatNum,LatNum);dataTmp_LON->get(Tmp_LON,LonNum,LonNum);dataTmp_UX->get(Tmp_UX,Time,LatNum,LonNum);dataTmp_VY->get(Tmp_VY,Time,LatNum,LonNum);for(int j = 0; j < n_yres; j ++)for(int i = 0; i < n_xres; i ++){ int index = ( (n_yres - 1 - j) * n_xres + i ) << 1;//int index = j*n_yres+i;pVectr[index ] = Tmp_UX[j*LonNum+i];pVectr[index +1 ]= Tmp_VY[j*LonNum+i];} delete []Tmp_UX;delete []Tmp_VY;delete []Tmp_LAT;}/// normalize the vector field ///
// void NormalizVectrs(int n_xres, int n_yres, float* pVectr)
// {
//
//
// for(int j = 0; j < n_yres; j ++)
// for(int i = 0; i < n_xres; i ++)
// {
// int index = (j * n_xres + i) << 1;
// float vcMag = float( sqrt( double(pVectr[index] * pVectr[index] + pVectr[index + 1] * pVectr[index + 1]) ) );
//
// float scale = (vcMag == 0.0f) ? 0.0f : 1.0f / vcMag;//矢量大小归一化后的矢量值
// //pVectr[index ] *= scale;
// pVectr[index ]=pVectr[index ]*scale;
// // cout<<"pVectr[index ]="<<pVectr[index ];
// pVectr[index + 1] *= scale;
// //cout<<"pVectr[index ]="<<pVectr[index +1 ];
//
// }
// }
void NormalizVectrs(int n_xres, int n_yres, float* pVectr,float* vecSize)
{ for(int j = 0; j < n_yres; j ++)for(int i = 0; i < n_xres; i ++){ int index = (j * n_xres + i) << 1;float vcMag = float( sqrt( double(pVectr[index] * pVectr[index] + pVectr[index + 1] * pVectr[index + 1]) ) );vecSize[j * n_xres + i]=vcMag;if (vcMag<10000&&vcMag>maxvecmag){maxvecmag=vcMag;}float scale = (vcMag == 0.0f) ? 0.0f : 1.0f / vcMag;pVectr[index ] *= scale*5.5;//????????????????????????????????????????????????????????????原来问题出在这pVectr[index + 1] *= scale*5.5;
// cout<<"pVectr["<<index<<"]=="<< pVectr[index]<<endl;
// cout<<"pVectr["<<index+1<<"]=="<< pVectr[index+1]<<endl;
// //fin>>index>>"=">>pVectr[index ] >>index+1>>pVectr[index+1]>>"/n"；}
}/// make white noise as the LIC input texture ///
// void MakeWhiteNoise(int n_xres, int n_yres, float* pNoise)
// {
// IplImage * NoiseImg=cvCreateImage(cvSize(n_xres,n_yres),IPL_DEPTH_8U,1);
// CvScalar s;
//
// for(int j = 0; j < n_yres; j ++)
// {
// for(int i = 0; i < n_xres; i ++)
//
// // for(int j = 0; j < n_yres; j=j +10)//产生稀疏白噪声
// // {
// // for(int i = 0; i < n_xres; i=i+10)
//
// {
// int r = rand();
// r = ( (r & 0xff) + ( (r & 0xff00) >> 8 ) ) & 0xff;
// pNoise[j * n_xres + i] = (float) r;
// s = cvGet2D(NoiseImg,i,j);
// s.val[0]=r;
// s.val[1]=r;
// s.val[2]=r;
// cvSet2D(NoiseImg,i,j,s);
// }
// }
//
// }void MakeWhiteNoise(int n_xres, int n_yres, float* pNoise)
{ for(int j = 0; j < n_yres; j ++)for(int i = 0; i < n_xres; i ++){ int r = rand();r = ( (r & 0xff) + ( (r & 0xff00) >> 8 ) ) & 0xff;pNoise[j * n_xres + i] = (float) r;}
}
/// generate box filter LUTs ///
void GenBoxFiltrLUT(int LUTsiz, float* p_LUT0, float* p_LUT1)
{ for(int i = 0; i < LUTsiz; i ++) p_LUT0[i] = p_LUT1[i] = i;
}void color(int n_xres,int n_yres, float* pImage,float* vecSize)
{IplImage * licImage = cvCreateImage(cvSize(n_xres,n_yres),IPL_DEPTH_8U,3);IplImage* img = cvLoadImage("11.jpg",1);int k = 0;double magind;double mag;double newMag;double x = 0.1;//x为非线性映射因子，且x！=1CvScalar colorTable[500];CvScalar s,s1;for (int i = 0;i < img->width;i++){s = cvGet2D(img,1,i);colorTable[i] =s;}for (int j=0;j<n_yres;j++){for (int i= 0;i<n_xres;i++){if (k>=img->width){k=0;}double scale= pImage[j * n_xres + i]/255.0f;成功生成彩色图像的关键mag = vecSize[j * n_xres + i];//********矢量大小归一化******if (mag<1000){magind = (mag/maxvecmag);}//非线性颜色增强LICnewMag =(pow(x,magind)-1)/(x-1);s = cvGet2D(licImage,j,i);//渐变颜色映射表int k = int(newMag*446); s1.val[0]=colorTable[k].val[0]*(k+1-newMag*446)+colorTable[k+1].val[0]*(newMag*446-k);s1.val[1]=colorTable[k].val[1]*(k+1-newMag*446)+colorTable[k+1].val[1]*(newMag*446-k);s1.val[2]=colorTable[k].val[2]*(k+1-newMag*446)+colorTable[k+1].val[2]*(newMag*446-k);s1.val[0]*=scale*2.1;?????????????????????????????????????可改s1.val[1]*=scale*2.1;s1.val[2]*=scale*2.1;// cout<<"s1.val[3]="<<s1.val[1]<<endl;cvSet2D(licImage,j,i,s1);}}//Mat AlphaImage= imread("s.jpg");//cv::Mat AlphaImage = imread("licImage",1);cvNamedWindow("lic_three channles",0);cvShowImage("lic_three channles",licImage);cvWaitKey(0);system("pause");cvDestroyWindow("lic_three channles");cvReleaseImage(&licImage);
}
/// write the LIC image to a PPM file ///
void WriteImage2PPM(int n_xres, int n_yres, float* pImage, char* f_name)
{ FILE* o_file;if( ( o_file = fopen(f_name, "w") ) == NULL ) { printf("Can't open output file\n"); return; }fprintf(o_file, "P6\n%d %d\n255\n", n_xres, n_yres);for(int j = 0; j < n_yres; j ++)for(int i = 0; i < n_xres; i ++){unsigned char unchar = pImage[j * n_xres + i];//某点像素的灰度纹理值fprintf(o_file, "%c%c%c", unchar, unchar, unchar);//}fclose (o_file); o_file = NULL;
}/// flow imaging (visualization) through Line Integral Convolution ///
void FlowImagingLIC(int n_xres, int n_yres, float* pVectr, float* pNoise, float* pImage, float* p_LUT0, float* p_LUT1, float krnlen)
{ int vec_id; ///ID in the VECtor buffer (for the input flow field)int advDir; ///ADVection DIRection (0: positive; 1: negative)int advcts; ///number of ADVeCTion stepS per direction (a step counter)int ADVCTS = int(krnlen * 3); ///MAXIMUM number of advection steps per direction to break dead loops //跳出死循环的条件float vctr_x; ///x-component of the VeCToR at the forefront pointfloat vctr_y; ///y-component of the VeCToR at the forefront pointfloat clp0_x; ///x-coordinate of CLiP point 0 (current)float clp0_y; ///y-coordinate of CLiP point 0 (current)float clp1_x; ///x-coordinate of CLiP point 1 (next )float clp1_y; ///y-coordinate of CLiP point 1 (next )float samp_x; ///x-coordinate of the SAMPle in the current pixelfloat samp_y; ///y-coordinate of the SAMPle in the current pixelfloat tmpLen; ///TeMPorary LENgth of a trial clipped-segmentfloat segLen; ///SEGment LENgthfloat curLen; ///CURrent LENgth of the streamlinefloat prvLen; ///PReVious LENgth of the streamline float W_ACUM; ///ACcuMulated Weight from the seed to the current streamline forefrontfloat texVal; ///TEXture VALuefloat smpWgt; ///WeiGhT of the current SaMPlefloat t_acum[2]; ///two ACcUMulated composite Textures for the two directions, perspectively 两个方向的卷积和float w_acum[2]; ///two ACcUMulated Weighting values for the two directions, perspectively 两个方向的权重和float* wgtLUT = NULL; ///WeiGhT Look Up Table pointing to the target filter LUT权重查找表float len2ID = (DISCRETE_FILTER_SIZE - 1) / krnlen; ///map a curve LENgth TO an ID in the LUT///for each pixel in the 2D output LIC image///for(int j = 0; j < n_yres; j ++)for(int i = 0; i < n_xres; i ++){ ///init the composite texture accumulators and the weight accumulators///每一个像素点为起始点，初始化一次权重和卷积和t_acum[0] = t_acum[1] = w_acum[0] = w_acum[1] = 0.0f;//初始化正反方向卷积和及权重和///for either advection direction///分别计算正反方向的卷积和及权重和for(advDir = 0; advDir < 2; advDir ++){ ///init the step counter, curve-length measurer, and streamline seed/////初始化当前方向上前进的步数和当前流线的总长advcts = 0;//前进的步数curLen = 0.0f;clp0_x = i + 0.5f;clp0_y = j + 0.5f;///access the target filter LUT///LUT显示查找表wgtLUT = (advDir == 0) ? p_LUT0 : p_LUT1;///until the streamline is advected long enough or a tightly spiralling center / focus is encountered///while( curLen < krnlen && advcts < ADVCTS ) //??????{///access the vector at the sample///vec_id = ( int(clp0_y) * n_xres + int(clp0_x) ) << 1;vctr_x = pVectr[vec_id ];vctr_y = pVectr[vec_id + 1];///in case of a critical point///遇到零向量，结束循环if( vctr_x == 0.0f && vctr_y == 0.0f ){ t_acum[advDir] = (advcts == 0) ? 0.0f : t_acum[advDir]; ///this line is indeed unnecessaryw_acum[advDir] = (advcts == 0) ? 1.0f : w_acum[advDir];break;}///negate the vector for the backward-advection case///相反的方向取相反的方向vctr_x = (advDir == 0) ? vctr_x : -vctr_x;vctr_y = (advDir == 0) ? vctr_y : -vctr_y;///clip the segment against the pixel boundaries --- find the shorter from the two clipped segments//////replace all if-statements whenever possible as they might affect the computational speed///segLen = LINE_SQUARE_CLIP_MAX;//cout<<"segLen="<<segLen<<endl;//cout<<"VECTOR_COMPONENT_MIN="<<LINE_SQUARE_CLIP_MAX<<endl;segLen = (vctr_x < -VECTOR_COMPONENT_MIN) ? ( int( clp0_x ) - clp0_x ) / vctr_x : segLen;//int（0.5）=0segLen = (vctr_x > VECTOR_COMPONENT_MIN) ? ( int( int(clp0_x) + 1.5f ) - clp0_x ) / vctr_x : segLen;segLen = (vctr_y < -VECTOR_COMPONENT_MIN) ? ( ( ( tmpLen = ( int( clp0_y) - clp0_y ) / vctr_y ) < segLen ) ? tmpLen : segLen ) : segLen;segLen = (vctr_y > VECTOR_COMPONENT_MIN) ?( ( ( tmpLen = ( int( int(clp0_y) + 1.5f ) - clp0_y ) / vctr_y ) < segLen ) ? tmpLen : segLen ) : segLen;///update the curve-length measurers///prvLen = curLen;curLen+= segLen;segLen+= 0.0004f;///check if the filter has reached either end///segLen = (curLen > krnlen) ? ( (curLen = krnlen) - prvLen ) : segLen;///obtain the next clip point///clp1_x = clp0_x + vctr_x * segLen;clp1_y = clp0_y + vctr_y * segLen;///obtain the middle point of the segment as the texture-contributing sample///samp_x = (clp0_x + clp1_x) * 0.5f;samp_y = (clp0_y + clp1_y) * 0.5f;///obtain the texture value of the sample///texVal = pNoise[ int(samp_y) * n_xres + int(samp_x) ];///update the accumulated weight and the accumulated composite texture (texture x weight)///W_ACUM = wgtLUT[ int(curLen * len2ID) ];smpWgt = W_ACUM - w_acum[advDir]; w_acum[advDir] = W_ACUM; t_acum[advDir] += texVal * smpWgt;///update the step counter and the "current" clip point///advcts ++;clp0_x = clp1_x;clp0_y = clp1_y;///check if the streamline has gone beyond the flow field///if( clp0_x < 0.0f || clp0_x >= n_xres || clp0_y < 0.0f || clp0_y >= n_yres) break;} }///normalize the accumulated composite texture///texVal = (t_acum[0] + t_acum[1]) / (w_acum[0] + w_acum[1]);///clamp the texture value against the displayable intensity range [0, 255]texVal = (texVal < 0.0f) ? 0.0f : texVal;texVal = (texVal > 255.0f) ? 255.0f : texVal; pImage[j * n_xres + i] = (float) texVal;
// if (j * n_xres + i>400000)
// {
// cout<<"pImage["<<j * n_xres + i<<"]="<<pImage[j * n_xres + i]<<endl;
// } }
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