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RedistOpenNI2Driverskinect.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 (), yuliyang@qq.com 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OpenNI 105 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 device 139 result = device.open( openni::ANY_DEVICE ); 140 CheckOpenNIError( result, "initialize context" ); 141 142 //creat depth stream 143 result = oniDepthStream.create( device, openni::SENSOR_DEPTH ); 144 CheckOpenNIError( result, "initialize context" ); 145 //set depth mode 146 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: removenoiserecord 319 * 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 down 431 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 else 445 { 446 break; 447 } 448 } 449 } 450 //go up 451 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 else 465 { 466 break; 467 } 468 } 469 } 470 } 471 else 472 { 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 else 485 { 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<<" 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 else 549 { 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 else 577 { 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 else 613 { 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 down 648 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 else 662 { 663 break; 664 } 665 } 666 } 667 //go up 668 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 else 682 { 683 break; 684 } 685 } 686 } 687 } 688 else 689 { 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 else 702 { 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 // else 752 // { 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<<" 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