【摘要】 提出区域差异性测度(DM),它反映一个像素点与它周围像素点的不协调程度,由此判断该点是否为噪声点。优化了DM的2个主要参数,并以此为基础提出了DM选点矢量中值滤波(DMNVM),即用DM判断移动窗口中心像素点是否为噪声点,若是利用矢量中值滤波(VMF)处理,否则保持原像素点不变。结果表明,DMNVM滤波性能明显优于现有的VMF、递进开关中值滤波(PSM)、标量中值滤波(SMF)、与标量中值距离最小向量滤波(MMVM)和方向矢量中值滤波(VDF);同近年提出的自适应向量滤波(AVMF)比较,AVMF客观指标平均绝对误差(MAE)、均方误差(MSE)和标准色差(NCD)分别是DMNVM的1.81、2.59和2.17倍,这说明DMNVM的滤波性能有显著提高。更多还原

【Abstract】 A new filter—DMNVM is proposed based on discrepancy measurement(DM).First,it is estimated to determine whether the moving window center pixel is a corrupted pixel.If the central pixel is corrupted,it will be processed by vector median filter(VMF);and if the central sample is noise-free,it remains unchanged.The performance of the proposed method is compared with that of the well-known vector standard filters such as the VMF,progressive switch median filter(PSM),scalar median filter(SMF),minimum distance between central sample and scalar median in its neighborhood vector median filter(MMVM) and the basic vector directional filter(VDF).The results show the proposed method is of excellent signal-detail preservation and effective impulse noise suppression.Moreover the values of objective criteria—mean absolute error(MAE),mean square error(MSE),and normalized color difference(NCD)of DMNVM are 0.81,1.59,1.17 times less than that of adaptive vector median filtering(AVMF) respectively.更多还原