数字图像处理前期上机20142ch

第三章空间域增强PointProcessing(GrayLevelTransforms)HistogramProcessingArithmeticProcessingNeighborProcessing邻域运算PointProcessingNeighborProcessing:

某坐标的输出值是输入图像同一坐标邻域的函数邻域运算PixelneighborpixelweightLinearweightedLinearspatialfiltering

Weightedfactors加权因子:w1,w2,w3,w4,w5,w6,w7,w8,w9Filter,mask,kernel,template,window,convolutionmask/kernel设H为线性函数/算子Sizeofmask:m*nm=2a+1,n=2b+1(a,b>=0integers)邻域运算Convolutioninvolves‘overlap–multiply–add’with‘convolutionmask’邻域运算对输出图像每个像素：将模板中心对准输入图像的相同像素；将模板所对应的像素与模板的权相乘；将所有的乘积相加，加和就是输出的像素值。g(x,y)=w(-1,-1)f(x-1,y-1)+w(-1,0)f(x-1,y)+w(-1,1)f(x-1,y+1)+w(0,-1)f(x,y-1)+w(0,0)f(x,y)+w(0,1)f(x,y+1)+w(1,-1)f(x+1,y-1)+w(1,0)f(x+1,y)+w(1,1)f(x+1,y+1)邻域运算012567156010120046030643252145123501615401/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/501/501/51/51/501/5001256715601012004603064325214512350161542/53/501/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/53/52/57/501/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/53/52/57/59/501/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/5352/57/59/51/501/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/53/52/57/59/51/59/501/501/51/51/501/50邻域运算01256715601012004603064325214512350161542/53/52/57/59/51/59/59/501/501/51/51/501/50邻域运算平滑SmoothingSpatialFilters锐化SharpeningSpatialFilters邻域运算Theaverageofpixels(avaraging/lowpassfilter):blurringandnoisereductionBox/MeanfilterWeightedaveragefilter邻域运算Howtoset(sum>0)Howtoimplement(2D=1D+1D)Howtoselectsize邻域运算1.Furtherincreaseinblurring(extremeblurringusedtoeliminatesmallobjects)2.Pronouncedblackborder邻域运算extremeblurringusedtoeliminatesmallobjects邻域运算GaussianNon-linearAnisotropicdiffusionfilter(各向异性散布滤波器)Othersmoothingfilter:邻域运算邻域运算-Gaussion滤波器邻域运算-Gaussion滤波器邻域运算-Gaussion滤波器邻域运算-Gaussion滤波器SmoothingSpatialFiltersSharpeningSpatialFilters邻域运算Thespatialdifferentiationofpixels:sharpening锐化滤波器Unsharpmaskingandhigh-boostfiltering:originsmooth锐化滤波器锐化滤波器锐化滤波器Derivative:锐化滤波器锐化滤波器Conclusion:(1)一阶导数边缘更宽(2)二阶导数对细节（孤立点、细线）更强(3)一阶导数对阶跃响应更强(4)二阶导数产生双边缘锐化滤波器二阶导数更适合图像增强，而一阶导数更适合边缘检测（参考图像分割）Laplacian:二阶Secondorder:锐化滤波器锐化滤波器中心为负negative中心为正positive锐化滤波器锐化滤波器锐化滤波器一阶梯度:锐化滤波器Robert:锐化滤波器锐化滤波器Homework1.线性点运算除了调节图像的对比度以外，还有一种典型的线性点运算的应用就是灰度标准化。假如设