C++ imageType_t::Assign方法代码示例

  //static
  void GradientsMergeMosaic::mergeMosaic(imageListType_t const & rImageList_p,
					 realType_t dBlackPoint_p,
					 pcl_enum eType_p,
					 int32 shrinkCount_p,
					 int32 featherRadius_p,
					 imageType_t &rResultImage_p,
					 sumMaskImageType_t &rSumMaskImage_p)
  {
    Assert(rImageList_p.Length()>=1);
    bool firstImage=true;
    int nCols=0,nRows=0,nChannels=0; /// size and color space of first image
    imageType_t::color_space colorSpace;
    weightImageType_t countImageDx, countImageDy; /// number of pixels that contributed to sumImageDx,Dy in average mode
    imageType_t sumImageDx, sumImageDy; /// combined gradients in x and y direction. Note: these gradients are *between* the pixels
                                        /// of the original image, so size is one less then original image is direction of derivative
    int nImages=0; /// number of images read
    const int enlargeSize=1; // number of pixels added at the border

    TimeMessage startMergeMosaic("Gradient Domain Merge Mosaic");

    TimeMessage startLoadImages("Loading images");
    for(std::size_t i=0;i<rImageList_p.Length();++i){
      imageType_t currentImage;
      int imageIndex=0;
      // allow for multi-image files
      while(loadFile(rImageList_p[i],imageIndex,currentImage)){
	++nImages;
	++imageIndex;
	// expand image dimensions so I have sufficient border for morpological transform and convolution
	TimeMessage startEnlarge("creating border");
	currentImage.CropBy(enlargeSize,enlargeSize,enlargeSize,enlargeSize);
	startEnlarge.Stop();

	if(firstImage){
	  firstImage=false;
	  // determine those parameters that must be shared by all images
	  nCols=currentImage.Width();
	  nRows=currentImage.Height();
	  nChannels=currentImage.NumberOfChannels();
	  colorSpace=currentImage.ColorSpace();

	  //allocate necessary helper images
	  rSumMaskImage_p.AllocateData(nCols,nRows);
	  rSumMaskImage_p.ResetSelections();
	  rSumMaskImage_p.Black();
	  sumImageDx.AllocateData(nCols-1,nRows,nChannels,colorSpace);
	  sumImageDx.ResetSelections();
	  sumImageDx.Black();
	  sumImageDy.AllocateData(nCols,nRows-1,nChannels,colorSpace);
	  sumImageDy.ResetSelections();
	  sumImageDy.Black();

	  countImageDx.AllocateData(nCols-1,nRows);
	  countImageDx.Black();
	  countImageDy.AllocateData(nCols,nRows-1);
	  countImageDy.Black();
	} else {
	  // FIXME I wonder if I should check color space etc as well...
	  // check if properties of this image are identical to those of the first image
	  if(nCols!=currentImage.Width()) {
	    throw Error("Current image width differs from first image width.");
	  } else if(nRows!=currentImage.Height()) {
	    throw Error("Current image height differs from first image height.");
	  }	else if(nChannels!=currentImage.NumberOfChannels()) {
	    throw Error("Current image number of channels differs from first image number of channels.");
	  }
	}
	TimeMessage startProcessImage("Processing Image"+String(nImages));
	mergeMosaicProcessImage(currentImage,dBlackPoint_p,eType_p,shrinkCount_p,featherRadius_p,sumImageDx, sumImageDy ,rSumMaskImage_p,countImageDx, countImageDy);
      }
    }
    startLoadImages.Stop();
    if (eType_p==GradientsMergeMosaicType::Average) {
      TimeMessage startAverage("Averaging images");
      averageImage(eType_p,countImageDx,sumImageDx);
      averageImage(eType_p,countImageDy,sumImageDy);
      // we do not need count images any longer
      countImageDx.AllocateData(0,0);
      countImageDy.AllocateData(0,0);
    }
    // at this point:
    // sumImageDx: Average or overlay of gradients of images read in x direction
    // sumImageDy: Average or overlay of gradients of images read in y direction
    // rSumMaskImage_p: mask with different values for the different sources of images. 0 is background.
    //              We use this later for information of the user, but it is not needed in the following process
    TimeMessage startMerge("Merging Images");
    imageType_t laplaceImage;
    TimeMessage startLaplace("Creating Laplace image");
    createLaplaceVonNeumannImage(sumImageDx,sumImageDy,laplaceImage);
    startLaplace.Stop();
    TimeMessage startSolve("Solving Laplace");
    solveImage(laplaceImage,rResultImage_p);
    startSolve.Stop();
    startMerge.Stop();
    rResultImage_p.ResetSelections();
#if 0
    // for debugging laplaceImage
    //    rResultImage_p.Assign(laplaceImage);
    rResultImage_p.Assign(sumImageDx);
//.........这里部分代码省略.........

  //static
  void GradientsHdrComposition::hdrComposition(imageListType_t const & rImageList_p,
					       bool bKeepLog_p,
					       realType_t dBias_p,
					       imageType_t &rResultImage_p,
					       numImageType_t &rDxImage_p,
					       numImageType_t &rDyImage_p)
  {
    Assert(rImageList_p.Length()>=1);
    bool firstImage=true;
    int nCols=0,nRows=0,nChannels=0; /// size and color space of first image
    imageType_t::color_space colorSpace;
    imageType_t sumImageDx, sumImageDy; /// combined gradients in x and y direction. Note: these gradients are *between* the pixels
                                        /// of the original image, so size is one less then original image is direction of derivative
    int nImages=0; /// number of images read
    const int enlargeSize=1; // number of pixels added at the border

    TimeMessage startHdrComposition("Gradient Domain Hdr Composition");

    TimeMessage startLoadImages("Loading images");
    for(std::size_t i=0;i<rImageList_p.Length();++i){
      imageType_t currentImage;
      int imageIndex=0;
      // allow for multi-image files
      while(loadFile(rImageList_p[i],imageIndex,currentImage)){
	++nImages;
	++imageIndex;
	// expand image dimensions so I have sufficient border for morpological transform and convolution
	TimeMessage startEnlarge("creating border");
	currentImage.CropBy(enlargeSize,enlargeSize,enlargeSize,enlargeSize);
	startEnlarge.Stop();

	if(firstImage){
	  firstImage=false;
	  // determine those parameters that must be shared by all images
	  nCols=currentImage.Width();
	  nRows=currentImage.Height();
	  nChannels=currentImage.NumberOfChannels();
	  colorSpace=currentImage.ColorSpace();

	  //allocate necessary helper images
	  rDxImage_p.AllocateData(nCols,nRows,nChannels,colorSpace);
	  rDxImage_p.ResetSelections();
	  rDxImage_p.Black();
	  rDyImage_p.AllocateData(nCols,nRows,nChannels,colorSpace);
	  rDyImage_p.ResetSelections();
	  rDyImage_p.Black();

	  sumImageDx.AllocateData(nCols-1,nRows,nChannels,colorSpace);
	  sumImageDx.ResetSelections();
	  sumImageDx.Black();
	  sumImageDy.AllocateData(nCols,nRows-1,nChannels,colorSpace);
	  sumImageDy.ResetSelections();
	  sumImageDy.Black();

	} else {
	  // FIXME I wonder if I should check color space etc as well...
	  // check if properties of this image are identical to those of the first image
	  if(nCols!=currentImage.Width()) {
	    throw Error("Current image width differs from first image width.");
	  } else if(nRows!=currentImage.Height()) {
	    throw Error("Current image height differs from first image height.");
	  }	else if(nChannels!=currentImage.NumberOfChannels()) {
	    throw Error("Current image number of channels differs from first image number of channels.");
	  }
	}
	TimeMessage startProcessImage("Processing Image"+String(nImages));
	hdrCompositionProcessImage(currentImage,nImages,dBias_p,0.0,1,sumImageDx, sumImageDy ,rDxImage_p,rDyImage_p);
      }
    }
    startLoadImages.Stop();
    // at this point:
    // sumImageDx: max log gradient of images read in x direction
    // sumImageDy: max log gradient of images read in y direction
    // rSumMaskImage_p: mask with different values for the different sources of images. 0 is background.
    //              We use this later for information of the user, but it is not needed in the following process
    TimeMessage startHdr("HDR Combining Images");
    imageType_t laplaceImage;
    TimeMessage startLaplace("Creating Laplace image");
    // eliminate gradients that come from singularities, i.e. <=0 pixels
    clipGradients(sumImageDx);
    clipGradients(sumImageDy);
    createLaplaceVonNeumannImage(sumImageDx,sumImageDy,laplaceImage);
    startLaplace.Stop();
    TimeMessage startSolve("Solving Laplace");
    solveImage(laplaceImage,rResultImage_p);
    startSolve.Stop();
    rResultImage_p.ResetSelections();
    if(!bKeepLog_p){
      TimeMessage startExp("Performing Exp()");
      realType_t dLogBias=std::log(1.0e-7);
      rResultImage_p.Rescale(dLogBias,0.0); //assumes result range is 1e-7..1
      expImage(rResultImage_p, rResultImage_p);
      startExp.Stop();
    }
    startHdr.Stop();
#if 0
    // for debugging laplaceImage
    //rResultImage_p.Assign(laplaceImage);
    rResultImage_p.Assign(sumImageDx);
//.........这里部分代码省略.........