VTK_Learning_图像平滑_均值滤波器_高斯滤波器__中值滤波器_各向异性滤波

喜欢ヅ旅行 2023-07-07 08:04 1阅读 0赞

# 1.均值滤波 #

> 均值滤波是一种经常用到的平滑方法，其对应的模板各个像素的值为1。在VTK中没有直接实现均值滤波的类，但是我们可以通过图像卷积运算来实现。卷积运算通过vtkImageConvolve类实现。通过vtkImageConvolve类，只需要设置相应的卷积模板，便可以实现多种空域图像滤波。
> 
> 下面代码说明了怎样使用vtkImageConvolve类来实现图像的均值滤波：  
>  
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageCast.h> //图像数据类型转换为计算类型
>     #include <vtkImageData.h>
>     #include <vtkImageConvolve.h>  //图像卷积运行
>     #include <vtkImageShiftScale.h> //设置像素值范围
>     //#include <vtkImageMandelbrotSource.h>
>     #include <vtkImageActor.h>
>     #include <vtkRenderer.h>
>     #include <vtkImageMandelbrotSource.h>
>     #include <vtkRenderWindow.h>
>     #include <vtkRenderWindowInteractor.h>
>     #include <vtkInteractorStyleImage.h>
>      
>     int main()
>     {
>     	vtkSmartPointer<vtkJPEGReader> reader =
>     		vtkSmartPointer<vtkJPEGReader>::New();
>     	reader->SetFileName("lena.jpg");
>     	reader->Update();
>      
>     	vtkSmartPointer<vtkImageCast> originalCastFilter =
>     		vtkSmartPointer<vtkImageCast>::New();
>     	originalCastFilter->SetInputConnection(reader->GetOutputPort()); //建管线
>     	originalCastFilter->SetOutputScalarTypeToFloat(); //设置属性
>     	originalCastFilter->Update();
>      
>     	vtkSmartPointer<vtkImageConvolve> convolveFilter =
>     		vtkSmartPointer<vtkImageConvolve>::New();
>     	convolveFilter->SetInputConnection(originalCastFilter->GetOutputPort()); //建管线
>      
>     	double kernel[25] = { 
>     		0.04, 0.04, 0.04, 0.04, 0.04,
>     		0.04, 0.04, 0.04, 0.04, 0.04,
>     		0.04, 0.04, 0.04, 0.04, 0.04,
>     		0.04, 0.04, 0.04, 0.04, 0.04,
>     		0.04, 0.04, 0.04, 0.04, 0.04 
>     	};
>     	convolveFilter->SetKernel5x5(kernel);
>     	convolveFilter->Update();
>      
>     	vtkSmartPointer<vtkImageCast> convCastFilter =
>     		vtkSmartPointer<vtkImageCast>::New();
>     	convCastFilter->SetInputData(convolveFilter->GetOutput());
>     	convCastFilter->SetOutputScalarTypeToUnsignedChar(); //转换为图像数据
>     	convCastFilter->Update();
>     	///
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> convolvedActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	convolvedActor->SetInputData(convCastFilter->GetOutput());
>     	
>     	double leftViewport[4] = { 0.0, 0.0, 0.5, 1.0 };
>     	double rightViewport[4] = { 0.5, 0.0, 1.0, 1.0 };
>      
>     	vtkSmartPointer<vtkRenderer> originalRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	originalRenderer->SetViewport(leftViewport);
>     	originalRenderer->AddActor(originalActor);
>     	originalRenderer->SetBackground(1.0, 1.0, 1.0);
>     	originalRenderer->ResetCamera();
>      
>     	vtkSmartPointer<vtkRenderer> convolvedRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	convolvedRenderer->SetViewport(rightViewport);
>     	convolvedRenderer->AddActor(convolvedActor);
>     	convolvedRenderer->SetBackground(1.0, 1.0, 1.0);
>     	convolvedRenderer->ResetCamera();
>     	
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();;
>     	rw->AddRenderer(originalRenderer);
>     	rw->AddRenderer(convolvedRenderer);
>     	rw->SetSize(640, 320);
>     	rw->Render();
>     	rw->SetWindowName("Smooth by MeanFilter");
>      
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Initialize();
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> 首先vtkJPEGReader对象读取一幅图像。考虑到进行卷积运算时数据范围的变化和精度要求，需要先将图像像素数据类型由unsigned char转换到float类型，该变换通过vtkImageCast实现，对应的设置函数SetOutputScalarTypeToFloat()。接下来需要定义卷积算子和卷积模板。vtkImageConvolve类实现图像的卷积运算，它需要两个输入。一个是需要进行卷积的图像，这里为vtkJPEGReader读取的图像数据，第二个是卷积模板数组。SetKernel5x5()函数接收一个5x5的卷积模板数组，即本例上定义的kernel数组。执行Update()后即可完成卷积运算。需要注意的是，卷积模板对应的系数之和应该为1，否则需要对计算结果进行归一化处理。另外该类中还定义了3x3和7x7的卷积模板设置函数，使用过程是一样的。卷积完成以后，再次通过vtkImageCast将float数据类型转换为unsigned char进行图像显示。  
> 均值滤波的结果如下：  
> ![20170128231306531][]

#  2.高斯滤波 #

> 高斯平滑的原理类似于均值滤波。均值滤波模板的系数都是一样的，而高斯平滑则是需要根据像素与模板中心的距离来定义权重。权重的计算方法是采用高斯分布，离中心越远，权重越小。
> 
> 下面是一个利用Gauss滤波进行图像平滑的实例：
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageCast.h>
>     #include <vtkImageData.h>
>     #include <vtkImageGaussianSmooth.h>
>     #include <vtkImageActor.h>
>     #include <vtkRenderer.h>
>     #include <vtkRenderWindow.h>
>     #include <vtkRenderWindowInteractor.h>
>     #include <vtkInteractorStyleImage.h>
>     //#include <vtkImageEllipsoidSource.h>
>      
>     int main()
>     {
>     	vtkSmartPointer<vtkJPEGReader> reader =
>     		vtkSmartPointer<vtkJPEGReader>::New();
>     	reader->SetFileName("lena.jpg");
>     	reader->Update();
>      
>     	vtkSmartPointer<vtkImageGaussianSmooth> gaussianSmoothFilter =
>     		vtkSmartPointer<vtkImageGaussianSmooth>::New();
>     	gaussianSmoothFilter->SetInputConnection(reader->GetOutputPort());
>     	gaussianSmoothFilter->SetDimensionality(2);
>     	gaussianSmoothFilter->SetRadiusFactor(5); //设置模板范围
>     	gaussianSmoothFilter->SetStandardDeviation(3);//正态分布/高斯分布标准差
>     	gaussianSmoothFilter->Update();
>      
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> smoothedActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	smoothedActor->SetInputData(gaussianSmoothFilter->GetOutput());
>      
>     	double originalViewport[4] = { 0.0, 0.0, 0.5, 1.0 };
>     	double smoothedViewport[4] = { 0.5, 0.0, 1.0, 1.0 };
>      
>     	vtkSmartPointer<vtkRenderer> originalRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	originalRenderer->SetViewport(originalViewport);
>     	originalRenderer->AddActor(originalActor);
>     	originalRenderer->ResetCamera();
>     	originalRenderer->SetBackground(1.0, 0, 0);
>      
>     	vtkSmartPointer<vtkRenderer> gradientMagnitudeRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	gradientMagnitudeRenderer->SetViewport(smoothedViewport);
>     	gradientMagnitudeRenderer->AddActor(smoothedActor);
>     	gradientMagnitudeRenderer->ResetCamera();
>     	gradientMagnitudeRenderer->SetBackground(1.0, 1.0, 1.0);
>      
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();
>     	rw->AddRenderer(originalRenderer);
>     	rw->AddRenderer(gradientMagnitudeRenderer);
>     	rw->SetSize(640, 320);
>     	rw->SetWindowName("Smooth by Gaussian");
>      
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Initialize();
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> vtkImageGaussianSmooth类默认是执行三维高斯滤波；  
> SetDimensionality()根据需要设置相应的维数；  
> SetRadiusFactor()用于设置高斯模板的大小，当超出该模板的范围时，系数取0；  
> SetStandardDeviation()用于设置高斯分布函数的标准差。  
> 高斯平滑效果如下所示：  
> ![20170128233032992][]

# 3.中值滤波 #

> vtkImageHybridMedian2D实现了对二维图像的中值滤波。其实现原理是，采用一个5x5的模板，逐次将模板中心对应于图像的每个像素上，将模板图像覆盖的像素的中值作为当前像素的输出值。
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageData.h>
>     #include <vtkImageCast.h>
>     #include <vtkImageHybridMedian2D.h>
>     #include <vtkImageActor.h>
>     #include <vtkRenderer.h>
>     #include <vtkRenderWindow.h>
>     #include <vtkRenderWindowInteractor.h>
>     #include <vtkInteractorStyleImage.h>
>      
>     int main(int argc, char* argv[])
>     {
>     	vtkSmartPointer<vtkJPEGReader> reader =
>     		vtkSmartPointer<vtkJPEGReader>::New();
>     	reader->SetFileName("lena.jpg");
>     	reader->Update();
>      
>     	vtkSmartPointer<vtkImageHybridMedian2D> hybridMedian =
>     		vtkSmartPointer<vtkImageHybridMedian2D>::New();
>     	hybridMedian->SetInputData(reader->GetOutput());
>     	hybridMedian->Update();
>     	///
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> hybridMedianActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	hybridMedianActor->SetInputData(hybridMedian->GetOutput());
>     	/
>     	double originalViewport[4] = { 0.0, 0.0, 0.5, 1.0 };
>     	double hybridMedianViewport[4] = { 0.5, 0.0, 1.0, 1.0 };
>      
>     	vtkSmartPointer<vtkRenderer> originalRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	originalRenderer->SetViewport(originalViewport);
>     	originalRenderer->AddActor(originalActor);
>     	originalRenderer->ResetCamera();
>     	originalRenderer->SetBackground(1.0,0,0);
>      
>     	vtkSmartPointer<vtkRenderer> hybridMedianRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	hybridMedianRenderer->SetViewport(hybridMedianViewport);
>     	hybridMedianRenderer->AddActor(hybridMedianActor);
>     	hybridMedianRenderer->ResetCamera();
>     	hybridMedianRenderer->SetBackground(1.0, 1.0, 1.0);
>     	//
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();
>     	rw->AddRenderer(originalRenderer);
>     	rw->AddRenderer(hybridMedianRenderer);
>     	rw->SetSize(640, 320);
>     	rw->Render();
>     	rw->SetWindowName("MedianFilterExample");
>      
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Initialize();
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> 该类使用非常简单，不需要用户设置任何参数。该方法能够有效的保持图像边缘，并对于椒盐噪声有较好的抑制作用。对于三维图像，则使用vtkImageHybridMedian3D类。
> 
> 执行结果如下：
> 
>  
> 
> ![20170128234214492][]

# 4.各向异性扩散滤波 #

> 高斯平滑方法在平滑噪声的同时，模糊了图像的重要边缘图像。  
> 各向异性滤波是一种基于偏微分方程的滤波技术，建立于热量的各向异性扩散理论。  
> 各向异性滤波在图像的平坦区域选择大尺度平滑，而边缘区域则选择小尺度的平滑，在抑制噪声的同时保持了图像的边缘信息。  
> vtkImageAnisotropicDiffusion2D(vtkImageAnisotropicDiffusion3D)实现图像各向异性扩散滤波，代码如下：  
>  
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageCast.h>
>     #include <vtkImageAnisotropicDiffusion2D.h>
>     #include <vtkImageActor.h>
>     #include <vtkCamera.h>
>     #include <vtkRenderer.h>
>     #include <vtkRenderWindow.h>
>     #include <vtkRenderWindowInteractor.h>
>     #include <vtkInteractorStyleImage.h>
>      
>     int main()
>     {
>     	vtkSmartPointer<vtkJPEGReader> reader =
>     		vtkSmartPointer<vtkJPEGReader>::New();
>     	reader->SetFileName("lena.jpg");
>      
>     	vtkSmartPointer<vtkImageAnisotropicDiffusion2D> diffusion =
>     		vtkSmartPointer<vtkImageAnisotropicDiffusion2D>::New();
>     	diffusion->SetInputConnection(reader->GetOutputPort());
>     	diffusion->SetNumberOfIterations(100);
>     	diffusion->SetDiffusionThreshold(5); //小于该阈值扩散
>     	diffusion->Update();
>     	/
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> diffusionActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	diffusionActor->SetInputData(diffusion->GetOutput());
>     	
>     	double leftViewport[4] = { 0.0, 0.0, 0.5, 1.0 };
>     	double rightViewport[4] = { 0.5, 0.0, 1.0, 1.0 };
>      
>     	vtkSmartPointer<vtkCamera> camera =
>     		vtkSmartPointer<vtkCamera>::New();
>     	vtkSmartPointer<vtkRenderer> leftRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	leftRenderer->SetViewport(leftViewport);
>     	leftRenderer->AddActor(originalActor);
>     	leftRenderer->SetBackground(1.0, 0, 0);
>     	leftRenderer->SetActiveCamera(camera);
>     	leftRenderer->ResetCamera();
>      
>     	vtkSmartPointer<vtkRenderer> rightRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	rightRenderer->SetViewport(rightViewport);
>     	rightRenderer->SetBackground(1.0, 1.0, 1.0);
>     	rightRenderer->AddActor(diffusionActor);
>     	rightRenderer->SetActiveCamera(camera);
>     	/
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();
>     	rw->AddRenderer(leftRenderer);
>     	rw->AddRenderer(rightRenderer);
>     	rw->SetSize(640, 320);
>     	rw->SetWindowName("Smooth by AnistropicFilter");
>      
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Initialize();
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> vtkImageAnisotropicDiffusion2D类通过迭代方法实现。  
> 其中SetNumberOfIterations()用于设置迭代的次数；  
> 各向异性扩散滤波原理是在梯度较小的像素处进行较大幅度扩散，而在大梯度处则只进行细微的扩散。因此需要设置一个扩算的阈值DiffusionThreshold，这个阈值与图像的梯度有关。SetDiffusionThreshold()即是用来设置扩散阈值。该类中还有一个梯度标志GradientMagnitudeThreshold，用来设置梯度算子。当该标志开时梯度通过中心差分方法计算；当标志为关时，需要单独处理每个相邻像素。当像素与相邻像素梯度小于DiffusionThreshold时进行扩散处理。  
> 下图是进行各向异性扩散滤波处理的结果：
> 
> ![20170129000416847][]

[20170128231306531]: https://img-blog.csdn.net/20170128231306531
[20170128233032992]: https://img-blog.csdn.net/20170128233032992
[20170128234214492]: https://img-blog.csdn.net/20170128234214492
[20170129000416847]: https://img-blog.csdn.net/20170129000416847