用kinect录视频库

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kinect深度视频去噪

kinectmod32.dll

http://pan.baidu.com/s/1DsGqX

下载后改名kinect.dll

替换掉Redist\OpenNI2\Drivers\kinect.dll

代码：

  1 /*  2  * =====================================================================================  3  *  4  *       Filename:  first_auoto_record.cpp  5  *  6  *    Description:    7  *    kinect自动录像，用于采集视频数据库，录制的视频每小段长为5min，（由子线程的模拟键盘延时决定，不同机器获取的视频长度不一样）  8  *  9  * 10  * 11  *        Version:  1.0 12  *        Created:  2013/10/14 16:37:10 13  *       Revision:  none 14  *       Compiler:  gcc 15  * 16  *         Author:  @礼杨_HDU (), [e-mail] 17  *   Organization:   18  * 19  * ===================================================================================== 20  */ 21 #include <stdlib.h>   22 #include <windows.h> 23 #include <iostream>   24 #include <conio.h> 25 #include <string>   26 #include "OpenNI.h"   27 #include "opencv2/core/core.hpp"   28 #include "opencv2/highgui/highgui.hpp"   29 #include "opencv2/imgproc/imgproc.hpp"   30  31 #define RESOLUTION 640,480 32 #define RECORDRESOLUTION 590,440 33 #define ADRESOLUTION 45,40,590,440 34 #define FPS 20 35 #define GRAYTH 10 36 #define REPAIRERANGE 5 37 #define COLORTH 10 38  39 using namespace std;   40 using namespace cv;   41 using namespace openni;   42 /*  43  * ===  FUNCTION  ====================================================================== 44  *         Name:  子线程 45  *  Description:   使用子进程给自己发送按键消息 46  * ===================================================================================== 47  */ 48 DWORD WINAPI ThreadFunction(LPVOID lpParameter) 49 { 50     printf("in thread......"); 51     while (TRUE){ 52         //your code 53  54         INPUT Input1 = { 0 }; 55         Input1.type       = INPUT_KEYBOARD; 56         Input1.mi.dwFlags = KEYEVENTF_EXTENDEDKEY; 57         Input1.ki.wVk   = 0x20; // 0 58         SendInput( 1, &Input1, sizeof( INPUT ) ); 59         INPUT Input2 = { 0 }; 60         Input2.type       = INPUT_KEYBOARD; 61         Input2.mi.dwFlags = KEYEVENTF_EXTENDEDKEY; 62         Input2.ki.wVk   = 0x0d; // 回车 63         SendInput( 1, &Input2, sizeof( INPUT ) ); 64         Sleep(300000);//每5分钟发送一个按键消息，即录下一段视频 65         } 66     return true; 67 } 68  69 /******************************************** 70                 Global variable 71 ********************************************/ 72 //Openni status 73 Status result = STATUS_OK;     74 // open device     75 Device device;   76 //OpenNI2 image   77 VideoFrameRef oniDepthImg;   78 VideoFrameRef oniColorImg;   79 // create stream    80 VideoStream oniDepthStream;   81 VideoStream oniColorStream;   82 // set video mode   83 VideoMode modeDepth;   84 VideoMode modeColor;   85 //OpenCV image   86 cv::Mat cvDepthImg;  87 cv::Mat cvDepthImg2; 88 cv::Mat cvColorImg;   89 cv::Mat cvColorImg2; 90 //OpenCV adjusted image 91 cv::Mat cvAdjustDepthImg; 92 cv::Mat cvAdjustColorImg; 93 //Resolution 94 Size se=Size(RESOLUTION); 95 Size recordse=Size(RECORDRESOLUTION); 96 /********************************************* 97                 function declaration 98 *********************************************/ 99 void CheckOpenNIError( Status result, string status )  100 {   101     if( result != STATUS_OK )   102         cerr << status << " Error: " << OpenNI::getExtendedError() << endl;  103 }  104 void iniOpenNI(void );//初始化OpenNI105 void releaseResource(void );//释放资源106 void OringinCapture(void );//107 void RemoveNoiseCapture(void );//108 void OringinRecord(void );//普通录制视频（640,480），录制深度视频（没有去噪）和彩色视频109 void RemoveNoiseRecord(void );//录制去噪后的视频，深度视频（未去噪）、深度视频（去噪）、彩色视频110 void RemoveNoise(void );//去除深度图像中的噪音111 bool pixelRepaire(int ,int ,int );//修复空洞像素点112 bool rangeRepaire(int ,int ,int );//范围修复113 void RepaireTest(void );114 void Test(void );115 116 117 int main( int argc, char** argv )  118 {  119     HANDLE hT=CreateThread(NULL,0,ThreadFunction,NULL,0,NULL);120     iniOpenNI();121     //OringinCapture();122     //RemoveNoiseCapture();123     //OringinRecord();124     125     RemoveNoiseRecord();126     releaseResource();127     //RepaireTest();128     //Test();129     return 0;  130 }131 //132 void iniOpenNI()133 {134     // initialize OpenNI2  135     result = OpenNI::initialize();  136     CheckOpenNIError( result, "initialize context" );    137 138     //open video device139     result = device.open( openni::ANY_DEVICE );  140     CheckOpenNIError( result, "initialize context" ); 141 142     //creat depth stream143     result = oniDepthStream.create( device, openni::SENSOR_DEPTH );  144     CheckOpenNIError( result, "initialize context" );    145     //set depth mode146     modeDepth.setResolution( RESOLUTION );  147     modeDepth.setFps( FPS );  148     modeDepth.setPixelFormat( PIXEL_FORMAT_DEPTH_1_MM );  149     oniDepthStream.setVideoMode(modeDepth);  150     // start depth stream  151     result = oniDepthStream.start();  152     CheckOpenNIError( result, "initialize context" );    153 154     // create color stream  155     result = oniColorStream.create( device, openni::SENSOR_COLOR );  156     CheckOpenNIError( result, "initialize context" );    157     // set color video mode  158     modeColor.setResolution( RESOLUTION );  159     modeColor.setFps( FPS );  160     modeColor.setPixelFormat( PIXEL_FORMAT_RGB888 );  161     oniColorStream.setVideoMode( modeColor);  162     // start color stream  163     result = oniColorStream.start();  164     CheckOpenNIError( result, "initialize context" );    165 166     // set depth and color imge registration mode  167     if( device.isImageRegistrationModeSupported(IMAGE_REGISTRATION_DEPTH_TO_COLOR ) )  168     {  169         cout << "support" << endl;170         device.setImageRegistrationMode( IMAGE_REGISTRATION_DEPTH_TO_COLOR );  171     }  172   173 }174 //175 void releaseResource()176 {177     //OpenNI2 destroy  178     oniDepthStream.destroy();  179     oniColorStream.destroy();  180     device.close();  181     OpenNI::shutdown();  182 }183 //184 void OringinCapture()185 {186     char DepthFilename[20];187     char ColorFilename[20];188     int n=0;189     while(true)190     {191         if( oniColorStream.readFrame( &oniColorImg ) == STATUS_OK )  192         {  193             // convert data into OpenCV type  194             cv::Mat cvRGBImg( oniColorImg.getHeight(), oniColorImg.getWidth(), CV_8UC3, (void*)oniColorImg.getData() );  195             cvtColor(cvRGBImg,cvColorImg,CV_RGB2GRAY);196             //cv::cvtColor( cvRGBImg, cvColorImg, CV_RGB2BGR );  197             //colorVideoWriter.write(cvColorImg);198         }  199         if( oniDepthStream.readFrame( &oniDepthImg ) == STATUS_OK )  200         {  201             cv::Mat cvRawImg16U( oniDepthImg.getHeight(), oniDepthImg.getWidth(), CV_16UC1, (void*)oniDepthImg.getData() );  202             cvRawImg16U.convertTo( cvDepthImg, CV_8UC1, 255.0/(oniDepthStream.getMaxPixelValue()));  203             //【5】  204             // convert depth image GRAY to BGR  205             //cv::cvtColor(cvDepthImg,cvDepthImg,CV_GRAY2BGR);  206             //depthVideoWriter.write(cvDepthImg);207         } 208         cvAdjustDepthImg=Mat(cvDepthImg,Rect(ADRESOLUTION));209         cvAdjustColorImg=Mat(cvColorImg,Rect(ADRESOLUTION));210         if(_kbhit())//_kbhit()211         {212             n++;213             sprintf(DepthFilename,"depthimage%03d.jpg",n);214             sprintf(ColorFilename,"colorimage%03d.jpg",n);215             imwrite(DepthFilename,cvAdjustDepthImg);216             imwrite(ColorFilename,cvAdjustColorImg);217             cout << "已经保存了" << n << "副图片" << endl;218             system("PAUSE");219         }220         imshow("depth",cvAdjustDepthImg);221         imshow("color",cvAdjustColorImg);222         waitKey(2);223     }224 }225 //226 void RemoveNoiseCapture()227 {228     char DepthFilename[20];229     char ColorFilename[20];230     int n=0;231     while(true)232     {233         if( oniColorStream.readFrame( &oniColorImg ) == STATUS_OK )  234         {  235             // convert data into OpenCV type  236             cv::Mat cvRGBImg( oniColorImg.getHeight(), oniColorImg.getWidth(), CV_8UC3, (void*)oniColorImg.getData() );  237             cvtColor(cvRGBImg,cvColorImg,CV_RGB2GRAY);238             //cv::cvtColor( cvRGBImg, cvColorImg, CV_RGB2BGR );  239             //colorVideoWriter.write(cvColorImg);240         }  241         if( oniDepthStream.readFrame( &oniDepthImg ) == STATUS_OK )  242         {  243             cv::Mat cvRawImg16U( oniDepthImg.getHeight(), oniDepthImg.getWidth(), CV_16UC1, (void*)oniDepthImg.getData() );  244             cvRawImg16U.convertTo( cvDepthImg, CV_8UC1, 255.0/(oniDepthStream.getMaxPixelValue()));  245             //【5】  246             // convert depth image GRAY to BGR  247             //cv::cvtColor(cvDepthImg,cvDepthImg,CV_GRAY2BGR);  248             //depthVideoWriter.write(cvDepthImg);249         } 250         cvAdjustDepthImg=Mat(cvDepthImg,Rect(ADRESOLUTION));251         cvAdjustColorImg=Mat(cvColorImg,Rect(ADRESOLUTION));252         if(_kbhit())//_kbhit()253         {254             n++;255             sprintf(DepthFilename,"depthimage%03d.jpg",n);256             sprintf(ColorFilename,"colorimage%03d.jpg",n);257             imwrite(DepthFilename,cvAdjustDepthImg);258             imwrite(ColorFilename,cvAdjustColorImg);259             cout << "已经保存了" << n << "副图片" << endl;260             system("PAUSE");261         }262         imshow("depth",cvAdjustDepthImg);263         imshow("color",cvAdjustColorImg);264         waitKey(2);265     }266 267 }268 //269 void OringinRecord()270 {271     int n=0;272     int operation;273     char DepthFilename[20];274     char ColorFilename[20];275     while(true)276     {277             n++;278             sprintf(DepthFilename,"oringindepthvideo%03d.avi",n);279             sprintf(ColorFilename,"oringincolorvideo%03d.avi",n);280             VideoWriter colorVideoWriter=VideoWriter(ColorFilename,CV_FOURCC('X','V','I','D'),FPS,se);281             VideoWriter depthVideoWriter=VideoWriter(DepthFilename,CV_FOURCC('X','V','I','D'),FPS,se);282             namedWindow("彩色图",1);  283             namedWindow("深度图",1);  284             while(true)   285             {    286                 if( oniColorStream.readFrame( &oniColorImg ) == STATUS_OK )  287                 {  288                     // convert data into OpenCV type  289                     cv::Mat cvRGBImg( oniColorImg.getHeight(), oniColorImg.getWidth(), CV_8UC3, (void*)oniColorImg.getData() );  290                     cv::cvtColor( cvRGBImg, cvColorImg, CV_RGB2BGR );  291                     colorVideoWriter.write(cvColorImg);292                     cv::imshow( "彩色图", cvColorImg );  293                 }  294                 if( oniDepthStream.readFrame( &oniDepthImg ) == STATUS_OK )  295                 {  296                     cv::Mat cvRawImg16U( oniDepthImg.getHeight(), oniDepthImg.getWidth(), CV_16UC1, (void*)oniDepthImg.getData() );  297                     cvRawImg16U.convertTo( cvDepthImg, CV_8UC1, 255.0/(oniDepthStream.getMaxPixelValue()));  298                     //【5】  299                     // convert depth image GRAY to BGR  300                     cv::cvtColor(cvDepthImg,cvDepthImg,CV_GRAY2BGR);  301                     depthVideoWriter.write(cvDepthImg);302                     cv::imshow( "深度图", cvDepthImg );  303                 }  304                 int key;305                 key=waitKey(100);306                 if(key==32)307                 {308                     break;309                 }310             }  311             destroyWindow("彩色图");  312             destroyWindow("深度图");  313             cout << "已经录制了" << n << "段视频" << endl;314     }315 }316 /* 317  * ===  FUNCTION  ======================================================================318  *         Name:  removenoiserecord319  *  Description:  包含录取彩色图像，去噪后的灰度图像，未去噪声的深度图像和去噪后的深度图像320  *321  * =====================================================================================322  */323 void RemoveNoiseRecord()324 {325     int n=0;326 327     char DepthFilename[20];328     char ColorFilename[20];329     char removeDepthFilename[20];330     char removeColorFilename[20];331     Mat t1;332     Mat t2;333     while(true)334     {335             n++;336             sprintf(removeDepthFilename,"removedepthvideo%03d.avi",n);337             sprintf(removeColorFilename,"removecolorvideo%03d.avi",n);338             sprintf(DepthFilename,"oringindepthvideo%03d.avi",n); /* 未去噪的深度图像 */339             sprintf(ColorFilename,"oringincolorvideo%03d.avi",n); /* 未去噪声的彩色图像 */340         341         342             VideoWriter removecolorVideoWriter=VideoWriter(removeColorFilename,CV_FOURCC('X','V','I','D'),FPS,recordse);343             VideoWriter removedepthVideoWriter=VideoWriter(removeDepthFilename,CV_FOURCC('X','V','I','D'),FPS,recordse);344         345             VideoWriter colorVideoWriter=VideoWriter(ColorFilename,CV_FOURCC('X','V','I','D'),FPS,se);346             VideoWriter depthVideoWriter=VideoWriter(DepthFilename,CV_FOURCC('X','V','I','D'),FPS,se);//347             namedWindow("去噪灰度图",1);  348             namedWindow("去噪深度图",1); 349             namedWindow("未去噪彩色图",1);  350             namedWindow("未去噪深度图",1);351             while(true)   352             {353                 if( oniColorStream.readFrame( &oniColorImg ) == STATUS_OK )  354                 {  355                     // convert data into OpenCV type  356                     cv::Mat cvRGBImg( oniColorImg.getHeight(), oniColorImg.getWidth(), CV_8UC3, (void*)oniColorImg.getData() );  357                     cv::cvtColor( cvRGBImg, cvColorImg2, CV_RGB2BGR );358                     cvColorImg2=Mat(cvColorImg2,Rect(ADRESOLUTION));359                     colorVideoWriter.write(cvColorImg2);360                     cv::imshow( "未去噪彩色图", cvColorImg2 ); 361                     cvtColor(cvRGBImg,cvColorImg,CV_RGB2GRAY);362                     //colorVideoWriter.write(cvColorImg);363                     364                 365                 }  366                 if( oniDepthStream.readFrame( &oniDepthImg ) == STATUS_OK )  367                 {  368                     cv::Mat cvRawImg16U( oniDepthImg.getHeight(), oniDepthImg.getWidth(), CV_16UC1, (void*)oniDepthImg.getData() );  369                     cvRawImg16U.convertTo( cvDepthImg, CV_8UC1, 255.0/(oniDepthStream.getMaxPixelValue()));  370                     cv::cvtColor(cvDepthImg,cvDepthImg2,CV_GRAY2BGR);  371                     cvDepthImg2=Mat(cvDepthImg2,Rect(ADRESOLUTION));372                     depthVideoWriter.write(cvDepthImg2);373                     cv::imshow( "未去噪深度图", cvDepthImg2 );  374                 } 375                 //调整图像尺寸376                 cvAdjustDepthImg=Mat(cvDepthImg,Rect(ADRESOLUTION));377                 cvAdjustColorImg=Mat(cvColorImg,Rect(ADRESOLUTION));378                 379             380             381                 RemoveNoise();382                 cvtColor(cvAdjustColorImg,cvAdjustColorImg,CV_GRAY2BGR);383                 cvtColor(cvAdjustDepthImg,cvAdjustDepthImg,CV_GRAY2BGR);384                 removecolorVideoWriter.write(cvAdjustColorImg);385                 removedepthVideoWriter.write(cvAdjustDepthImg);386                 imshow("去噪灰度图",cvAdjustColorImg);387                 imshow("去噪深度图",cvAdjustDepthImg);388                 int key;389                 key=waitKey(10);390                 if(key==32)391                 {392                     break;393                 }394             }395             destroyWindow("去噪灰度图");  396             destroyWindow("去噪深度图");  397             destroyWindow("未去噪彩色图");  398             destroyWindow("未去噪深度图");  399             400             cout << "已经录制了" << n << "段视频" << endl;401     }402 }403 //404 void RemoveNoise()405 {406     clock_t start,finish;407     double totaltime=0.0;408     start=clock();409 410     for(int j=(cvAdjustDepthImg.rows-1);j>=0;j--)//depthImage.rows，行数411     {412         const uchar* mj=cvAdjustDepthImg.ptr<uchar>(j);413         for(int i=(cvAdjustDepthImg.cols-1);i>=0;i--)//depthImage.cols，列数414         {415             //修复空洞416             if(mj[i]<=GRAYTH)417             {418                 uchar colorpixel=cvAdjustColorImg.at<uchar>(j,i);419                 bool reResult=false;420                 //分黑色和非黑色区域分开处理421                 if(colorpixel<GRAYTH*5)422                 {423                     //像素点修复424                     for(int k=1;k<REPAIRERANGE*3;k++)425                     {426                         reResult=pixelRepaire(i,j,k);427                         if(reResult)428                             break;429                     }430                     //go down431                     if(!reResult)432                     {433                         for(int k=1;k<=30;k++)434                         {435                             if((j+k)<440)436                             {437                                 if(cvAdjustDepthImg.at<uchar>(j+k,i)>GRAYTH)438                                 {439                                     cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j+k,i);440                                     reResult=true;441                                     break;442                                 }443                             }444                             else445                             {446                                 break;447                             }448                         }449                     }450                     //go up451                     if(!reResult)452                     {453                         for(int k=1;k<=30;k++)454                         {455                             if((j-k)>=0)456                             {457                                 if(cvAdjustDepthImg.at<uchar>(j-k,i)>GRAYTH)458                                 {459                                     cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j-k,i);460                                     reResult=true;461                                     break;462                                 }463                             }464                             else465                             {466                                 break;467                             }468                         }469                     }470                 }471                 else472                 {473                     //消除物体边界的噪音474                     for(int k=1;k<30;k++)475                     {476                         if((i+k)<590 && !reResult)477                         {478                             if(abs(cvAdjustColorImg.at<uchar>(j,i+k)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(j,i+k)>GRAYTH)479                             {480                                 cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j,i+k);481                                 reResult=true;482                             }483                         }484                         else485                         {486                             break;487                         }488                     }    489                 }490                 //像素点周围寻找可利用点（考虑彩色图像是否匹配）491                 if(!reResult)492                 {493                     for(int k=1;k<REPAIRERANGE;k++)494                     {495                         reResult=pixelRepaire(i,j,k);496                         if(reResult)497                             break;498                     }499                 }500                 //范围寻找可利用点（不管彩色图像是否匹配）501                 if(!reResult)502                 {503                     for(int k=0;k<REPAIRERANGE*3;k++)504                     {505                         reResult=rangeRepaire(i,j,k);506                         if(reResult)507                             break;508                     }509                 }510             }511         }512     }513 514 515     finish=clock();516     totaltime=(double)(finish-start)/CLOCKS_PER_SEC;517     //cout<<"\n此帧图像的去噪时间为"<< totaltime << "秒！"<< endl;518 }519 //像素点修复520 bool pixelRepaire(int i,int j,int repaireRange)521 {522     uchar colorpixel=cvAdjustColorImg.at<uchar>(j,i);523     int x=0;524     int y=0;525     int n=0;//符合要求的点的数量526     int sum=0;//符合要求的点的灰度值的和527     for(y=j-repaireRange;y<=j+repaireRange;y++)528     {529         if(y>=0 && y<440)530         {531             //上下边界寻找532             if(y==(j-repaireRange) ||  y==(j+repaireRange))533             {534                 for(x=i-repaireRange;x<=i+repaireRange;x++)535                 {536                     if(x>=0 && x<590)537                     {538                         if(abs(cvAdjustColorImg.at<uchar>(y,x)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(y,x)>GRAYTH)539                         {540                             n++;541                             sum=sum+cvAdjustDepthImg.at<uchar>(y,x);542                         }543                     }544 545                 }546             }547             //左右边界寻找548             else549             {550                 //左551                 x=i-repaireRange;552                 if(x>=0 && x<590)553                 {554                     if(abs(cvAdjustColorImg.at<uchar>(y,x)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(y,x)>GRAYTH)555                     {556                         n++;557                         sum=sum+cvAdjustDepthImg.at<uchar>(y,x);558                     }559                 }560                 //右561                 x=i+repaireRange;562                 if(x>=0 && x<590)563                 {564                     if(abs(cvAdjustColorImg.at<uchar>(y,x)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(y,x)>GRAYTH)565                     {566                         n++;567                         sum=sum+cvAdjustDepthImg.at<uchar>(y,x);568                     }569                 }570             }571         }572         573     }574     if(n<repaireRange*2)575     {return false;}576     else577     {578         cvAdjustDepthImg.at<uchar>(j,i)=(uchar)(sum/n);579         return true;580     }581 582 }583 //范围性修复584 bool rangeRepaire(int i,int j,int repaireRange)585 {586     uchar colorpixel=cvAdjustColorImg.at<uchar>(j,i);587     int x=0;588     int y=0;589     int n=0;590     int sum=0;591     for(y=j-repaireRange;y<=j+repaireRange;y++)592     {593         if(y>=0 && y<440)594         {595             for(x=i-repaireRange;x<=i+repaireRange;x++)596             {597                 if(x>=0 && x<590)598                 {599                     if(cvAdjustDepthImg.at<uchar>(y,x)>GRAYTH)600                     {601                         n++;602                         sum=sum+cvAdjustDepthImg.at<uchar>(y,x);603                     }604                 }605             }606         }607     }608     if(n<=repaireRange*2)609     {610         return false;611     }612     else613     {614         cvAdjustDepthImg.at<uchar>(j,i)=(uchar)(sum/n);615         return true;616     }617 }618 //619 void RepaireTest()620 {621     cvAdjustColorImg=imread("colorimage005.jpg",0);622     cvAdjustDepthImg=imread("depthimage005.jpg",0);623     Mat oriDepthImg=cvAdjustDepthImg.clone();624     clock_t start,finish;625     double totaltime=0.0;626     start=clock();627     for(int j=(cvAdjustDepthImg.rows-1);j>=0;j--)//depthImage.rows，行数628     {629         const uchar* mj=cvAdjustDepthImg.ptr<uchar>(j);630         for(int i=(cvAdjustDepthImg.cols-1);i>=0;i--)//depthImage.cols，列数631         {632             //修复空洞633             if(mj[i]<=GRAYTH)634             {635                 uchar colorpixel=cvAdjustColorImg.at<uchar>(j,i);636                 bool reResult=false;637                 //分黑色和非黑色区域分开处理638                 if(colorpixel<GRAYTH*5)639                 {640                     //像素点修复641                     for(int k=1;k<REPAIRERANGE*3;k++)642                     {643                         reResult=pixelRepaire(i,j,k);644                         if(reResult)645                             break;646                     }647                     //go down648                     if(!reResult)649                     {650                         for(int k=1;k<=30;k++)651                         {652                             if((j+k)<440)653                             {654                                 if(cvAdjustDepthImg.at<uchar>(j+k,i)>GRAYTH)655                                 {656                                     cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j+k,i);657                                     reResult=true;658                                     break;659                                 }660                             }661                             else662                             {663                                 break;664                             }665                         }666                     }667                     //go up668                     if(!reResult)669                     {670                         for(int k=1;k<=30;k++)671                         {672                             if((j-k)>=0)673                             {674                                 if(cvAdjustDepthImg.at<uchar>(j-k,i)>GRAYTH)675                                 {676                                     cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j-k,i);677                                     reResult=true;678                                     break;679                                 }680                             }681                             else682                             {683                                 break;684                             }685                         }686                     }687                 }688                 else689                 {690                     //消除物体边界的噪音691                     for(int k=1;k<30;k++)692                     {693                         if((i+k)<590 && !reResult)694                         {695                             if(abs(cvAdjustColorImg.at<uchar>(j,i+k)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(j,i+k)>GRAYTH)696                             {697                                 cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j,i+k);698                                 reResult=true;699                             }700                         }701                         else702                         {703                             break;704                         }705                     }    706                 }707                 //像素点周围寻找可利用点（考虑彩色图像是否匹配）708                 if(!reResult)709                 {710                     for(int k=1;k<REPAIRERANGE;k++)711                     {712                         reResult=pixelRepaire(i,j,k);713                         if(reResult)714                             break;715                     }716                 }717                 //范围寻找可利用点（不管彩色图像是否匹配）718                 if(!reResult)719                 {720                     for(int k=0;k<REPAIRERANGE*3;k++)721                     {722                         reResult=rangeRepaire(i,j,k);723                         if(reResult)724                             break;725                     }726                 }727              }728         }729     }730 //     for(int j=(cvAdjustDepthImg.rows-1);j>=0;j--)//depthImage.rows，行数731 //     {732 //         const uchar* mj=cvAdjustDepthImg.ptr<uchar>(j);733 //         for(int i=(cvAdjustDepthImg.cols-1);i>=0;i--)//depthImage.cols，列数734 //         {735 //             //修复空洞736 //             if(mj[i]<=GRAYTH)737 //             {738 //                 uchar colorpixel=cvAdjustColorImg.at<uchar>(j,i);739 //                 bool reResult=false;740 //                 //从右向左寻找可利用点 741 //                 for(int k=1;k<30;k++)742 //                 {743 //                     if((i+k)<590 && !reResult)744 //                     {745 //                         if(abs(cvAdjustColorImg.at<uchar>(j,i+k)-colorpixel)<=COLORTH && cvAdjustDepthImg.at<uchar>(j,i+k)>GRAYTH)746 //                         {747 //                             cvAdjustDepthImg.at<uchar>(j,i)=cvAdjustDepthImg.at<uchar>(j,i+k);748 //                             reResult=true;749 //                         }750 //                     }751 //                     else752 //                     {753 //                         break;754 //                     }755 //                 }    756 //                 //像素点修复757 //                 if(!reResult)758 //                 {759 //                     for(int k=1;k<REPAIRERANGE;k++)760 //                     {761 //                         reResult=pixelRepaire(i,j,k);762 //                         if(reResult)763 //                             break;764 //                     }765 //                 }766 //             }767 //         }768 //     }769     //ccc=cvAdjustDepthImg.clone();770     /*771     for(int j=(cvAdjustDepthImg.rows-1);j>=0;j--)//depthImage.rows，行数772     {773         const uchar* mj=cvAdjustDepthImg.ptr<uchar>(j);774         for(int i=(cvAdjustDepthImg.cols-1);i>=0;i--)//depthImage.cols，列数775         {776             //修复空洞777             if(mj[i]<=GRAYTH)778             {779                 bool reResult;780                 for(int k=1;k<=REPAIRERANGE;k++)781                 {782                     reResult=rangeRepaire(i,j,k);783                     if(reResult)784                         break;785                 }786             }787         }788     }789     */790     //Mat xxx;791     //Mat zzz=cvAdjustDepthImg.clone();792     //GaussianBlur(cvAdjustDepthImg,xxx,Size(3,3),0,0);793     //bilateralFilter(cvAdjustDepthImg,xxx,3,5*2,5*2);794     finish=clock();795     totaltime=(double)(finish-start)/CLOCKS_PER_SEC;796     cout<<"\n此帧图像的去噪时间为"<< totaltime << "秒！"<< endl;797     imshow("去噪深度",cvAdjustDepthImg);798     imshow("深度",oriDepthImg);799     imshow("彩色",cvAdjustColorImg);800     waitKey();801     //system("PAUSE");802 803 }804 //805 void Test()806 {807     //cvColorImg=imread("colorimage003.jpg",0);808     //cout << (int)cvColorImg.at<uchar>(369,272) << endl ;809     //cout << (int)cvColorImg.at<uchar>(73,394) << endl ;810     //cout << (int)cvColorImg.at<uchar>(428,256) << endl ;811     //cout << (int)cvColorImg.at<uchar>(326,553) << endl ;812     cvAdjustColorImg=imread("colorimage003.jpg",0);813     cvAdjustDepthImg=imread("depthimage003.jpg",0);814     Mat t;815     addWeighted(cvAdjustDepthImg,0.8,cvAdjustColorImg,0.2,0,t);816     imshow("1",t);817     waitKey();818 }

在录视频中遇到的一个问题是录成的视频只有6K大小，花了我半天时间，原来是窗口大小的问题。

如果录取的原视频的大小也是要调整为

 RECORDRESOLUTION 590,440的话colorVideoWriter里的参数不能为se,应该为 recordse否则就会有6k问题