VTK_Learning_频域处理_高通滤波（理想+巴特沃兹）

比眉伴天荒 2023-07-10 12:49 9阅读 0赞

# 1.理想高通滤波器 #

> 高通滤波与低通滤波正好相反，是频域图像的高频部分通过而抑制低频部分。在图像中图像的边缘对应高频分量，因此高通滤波的效果是图像锐化。同样最简单的高通滤波器是理想高通滤波器。通过设置一个频率阈值，将高于该阈值的频率部分通过，而低于阈值的低频部分设置为0。
> 
> VTK中理想高通滤波的实例如下：
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageFFT.h>
>     #include <vtkImageIdealHighPass.h>
>     #include <vtkImageRFFT.h>
>     #include <vtkImageCast.h>
>     #include <vtkImageExtractComponents.h>
>     #include <vtkRenderer.h>
>     #include <vtkImageActor.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<vtkImageFFT> fftFilter =
>     		vtkSmartPointer<vtkImageFFT>::New();
>     	fftFilter->SetInputConnection(reader->GetOutputPort());
>     	fftFilter->Update();
>      
>     	vtkSmartPointer<vtkImageIdealHighPass> highPassFilter =
>     		vtkSmartPointer<vtkImageIdealHighPass>::New();
>     	highPassFilter->SetInputConnection(fftFilter->GetOutputPort());
>     	highPassFilter->SetXCutOff(0.1);
>     	highPassFilter->SetYCutOff(0.1);
>     	highPassFilter->Update();
>      
>     	vtkSmartPointer<vtkImageRFFT> rfftFilter =
>     		vtkSmartPointer<vtkImageRFFT>::New();
>     	rfftFilter->SetInputConnection(highPassFilter->GetOutputPort());
>     	rfftFilter->Update();
>      
>     	vtkSmartPointer<vtkImageExtractComponents> ifftExtractReal =
>     		vtkSmartPointer<vtkImageExtractComponents>::New();
>     	ifftExtractReal->SetInputConnection(rfftFilter->GetOutputPort());
>     	ifftExtractReal->SetComponents(0);
>      
>     	vtkSmartPointer<vtkImageCast> castFilter =
>     		vtkSmartPointer<vtkImageCast>::New();
>     	castFilter->SetInputConnection(ifftExtractReal->GetOutputPort());
>     	castFilter->SetOutputScalarTypeToUnsignedChar();
>     	castFilter->Update();
>     	/
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> erodedActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	erodedActor->SetInputData(castFilter->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> leftRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	leftRenderer->AddActor(originalActor);
>     	leftRenderer->SetViewport(leftViewport);
>     	leftRenderer->SetBackground(1.0, 1.0, 1.0);
>     	leftRenderer->ResetCamera();
>     	vtkSmartPointer<vtkRenderer> rightRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	rightRenderer->AddActor(erodedActor);
>     	rightRenderer->SetViewport(rightViewport);
>     	rightRenderer->SetBackground(1.0, 1.0, 1.0);
>     	rightRenderer->ResetCamera();
>     	/
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();
>     	rw->SetSize(640, 320);
>     	rw->AddRenderer(leftRenderer);
>     	rw->AddRenderer(rightRenderer);
>     	rw->SetWindowName("IdealHighPassExample");
>      
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> 同低通滤波一样，首先将读入图像通过vtkImageFFT转换到频域空间，定义vtkImageIdealHighPass对象，并通过SetXCutOff ()和SetYCutOff() 设置X和Y方向的截止频率。然后通过vtkImageRFFT将处理后的图像转换到空域中，得到高通滤波图像。为了显示的需要，还需要提取图像分量和数据类型的转换。
> 
>   
> 下面是理想高通滤波的执行结果：
> 
> ![20170129142123522][]
> 
> 从结果看出高通滤波后图像得到锐化处理，图像中仅剩下边缘。

# 2.巴特沃兹高通滤波  #

> 理想高通滤波器不能通过电子元器件来实现，而且存在振铃现象。在实际中最常使用的高通滤波器是巴特沃斯高通滤波器。该滤波器的转移函数是：
> 
> ![20170129142350072][]
> 
>  
> 
> D(u,v)表示频域中点到频域平面的距离，是截止频率。当D(u,v)大于时，对应的H(u,v)逐渐接近1，从而使得高频部分得以通过；而当D(u,v)小于时，H(u,v)逐渐接近0，实现低频部分过滤。巴特沃斯高通滤波器在VTK中对应vtkImageButterworthHighPass类。
> 
> 下面代码说明了vtkImageButterworthHighPass对图像进行高通滤波：
> 
>     #include <vtkAutoInit.h>
>     VTK_MODULE_INIT(vtkRenderingOpenGL);
>      
>     #include <vtkSmartPointer.h>
>     #include <vtkJPEGReader.h>
>     #include <vtkImageFFT.h>
>     #include <vtkImageButterworthHighPass.h>
>     #include <vtkImageRFFT.h>
>     #include <vtkImageExtractComponents.h>
>     #include <vtkImageCast.h>
>     #include <vtkRenderer.h>
>     #include <vtkImageActor.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<vtkImageFFT> fftFilter =
>     		vtkSmartPointer<vtkImageFFT>::New();
>     	fftFilter->SetInputConnection(reader->GetOutputPort());
>     	fftFilter->Update();
>      
>     	vtkSmartPointer<vtkImageButterworthHighPass> highPassFilter =
>     		vtkSmartPointer<vtkImageButterworthHighPass>::New();
>     	highPassFilter->SetInputConnection(fftFilter->GetOutputPort());
>     	highPassFilter->SetXCutOff(0.1);
>     	highPassFilter->SetYCutOff(0.1);
>     	highPassFilter->Update();
>      
>     	vtkSmartPointer<vtkImageRFFT> rfftFilter =
>     		vtkSmartPointer<vtkImageRFFT>::New();
>     	rfftFilter->SetInputConnection(highPassFilter->GetOutputPort());
>     	rfftFilter->Update();
>      
>     	vtkSmartPointer<vtkImageExtractComponents> ifftExtractReal =
>     		vtkSmartPointer<vtkImageExtractComponents>::New();
>     	ifftExtractReal->SetInputConnection(rfftFilter->GetOutputPort());
>     	ifftExtractReal->SetComponents(0);
>      
>     	vtkSmartPointer<vtkImageCast> castFilter =
>     		vtkSmartPointer<vtkImageCast>::New();
>     	castFilter->SetInputConnection(ifftExtractReal->GetOutputPort());
>     	castFilter->SetOutputScalarTypeToUnsignedChar();
>     	castFilter->Update();
>     	
>     	vtkSmartPointer<vtkImageActor> originalActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	originalActor->SetInputData(reader->GetOutput());
>      
>     	vtkSmartPointer<vtkImageActor> erodedActor =
>     		vtkSmartPointer<vtkImageActor>::New();
>     	erodedActor->SetInputData(castFilter->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> leftRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	leftRenderer->AddActor(originalActor);
>     	leftRenderer->ResetCamera();
>     	leftRenderer->SetViewport(leftViewport);
>     	leftRenderer->SetBackground(1.0, 1.0, 1.0);
>      
>     	vtkSmartPointer<vtkRenderer> rightRenderer =
>     		vtkSmartPointer<vtkRenderer>::New();
>     	rightRenderer->AddActor(erodedActor);
>     	rightRenderer->SetViewport(rightViewport);
>     	rightRenderer->SetBackground(1.0, 1.0, 1.0);
>     	rightRenderer->ResetCamera();
>     	
>     	vtkSmartPointer<vtkRenderWindow> rw =
>     		vtkSmartPointer<vtkRenderWindow>::New();
>     	rw->AddRenderer(leftRenderer);
>     	rw->AddRenderer(rightRenderer);
>     	rw->SetSize(640, 320);
>     	rw->Render();
>     	rw->SetWindowName("Frequency_ButterworthHighPass");
>     	/
>     	vtkSmartPointer<vtkRenderWindowInteractor> rwi =
>     		vtkSmartPointer<vtkRenderWindowInteractor>::New();
>     	vtkSmartPointer<vtkInteractorStyleImage> style =
>     		vtkSmartPointer<vtkInteractorStyleImage>::New();
>     	rwi->SetInteractorStyle(style);
>     	rwi->SetRenderWindow(rw);
>     	rwi->Start();
>      
>     	return 0;
>     }
> 
> vtkImageButterworthHighPass与理想高通滤波使用方法一致。需要设置X和Y轴的截止频率，为了便于比较，其截止频域与理想高通滤波设置一致。

下图是执行结果：

![20170129143501170][]

[20170129142123522]: https://img-blog.csdn.net/20170129142123522
[20170129142350072]: https://img-blog.csdn.net/20170129142350072
[20170129143501170]: https://img-blog.csdn.net/20170129143501170