使用NPP的锐化掩模

时间:2014-03-18 06:12:09

标签: image-processing gpu npp

我尝试使用NPP创建一个"非锐化的面具"但我的形象并没有变得尖锐,在某些地区只是稍微亮一点。知道这段代码有什么问题吗?

    npp::loadImage("Lena.pgm", hostSrc);

    // put two copies of the image in GPU memory
    // one we'll turn into the unsharp mask                                                                                                                      
    npp::ImageNPP_8u_C1 deviceSrc(hostSrc);
    npp::ImageNPP_8u_C1 deviceUnsharpMask(hostSrc);

    // 5x5 box for mask 
    NppiSize maskSize = {5, 5};

    // create ROI based on image size and mask size                                                                                              
    NppiSize maskedROI = {deviceSrc.width() - maskSize.width + 1,
                          deviceSrc.height() - maskSize.height + 1};

    // allocate device blurred image                                                                                              
    npp::ImageNPP_8u_C1 deviceBlurred(maskedROI.width, maskedROI.height);

    NppiPoint anchor = {0, 0};

    // run box filter                                                                                                                                     
    nppiFilterBox_8u_C1R(deviceSrc.data(), deviceSrc.pitch(),
                         deviceBlurred.data(), deviceBlurred.pitch(),
                         maskedROI, maskSize, anchor);

    // subtract the masked image from the scratch image                                                                                                   
    eStatusNPP = nppiSub_8u_C1IRSfs(deviceBlurred.data(), deviceBlurred.pitch(),
                                    deviceUnsharpMask.data(), deviceUnsharpMask.pitch(),
                                    maskedROI, 1);


    // now add the mask to the src image                                                                                                                  
    eStatusNPP = nppiAdd_8u_C1IRSfs(deviceUnsharpMask.data(), deviceUnsharpMask.pitch(),
                                    deviceSrc.data(), deviceSrc.pitch(),
                                    maskedROI, 0);

    // then copy back to host and save to file

1 个答案:

答案 0 :(得分:-1)

钝化蒙版的工作原理如下:

  1. 模糊原始图像 - 我们称之为BI。
  2. 从原始图像中减去模糊图像(详细信息) - DI = OI - BI。
  3. 放大细节并将其添加到原始图像 - USMI = OI + alpha * DI。
  4. 你确定这是你做的吗?

    这是参考MATLAB代码:

    function [ mUsmImage ] = Usm( mInputImage, usmAmount, usmRadius )
    
    gaussianKernelRadius = ceil(6 * usmRadius);
    
    mGaussianKernel = exp(-([-gaussianKernelRadius:gaussianKernelRadius] .^ 2) / (2 * usmRadius * usmRadius));
    
    mGaussianKernel = mGaussianKernel.' * mGaussianKernel;
    mGaussianKernel = mGaussianKernel / sum(mGaussianKernel(:));
    
    mBlurredLayer = imfilter(mInputImage, mGaussianKernel, 'replicate');
    
    mUsmImage = mInputImage + (usmAmount * (mInputImage - mBlurredLayer ));
    
    end
    

    该代码适用于灰度图像。 它可以很容易地用于RGB。

    享受。