UNIQUENESS OF THE GAUSSIAN KERNEL FOR SCALE-SPACE FILTERING
UNIQUENESS OF THE GAUSSIAN KERNEL FOR SCALE-SPACE FILTERING
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DOI：
10.1109/tpami.1986.4767749
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发表时间：
1986-01-01
影响因子：
23.6
通讯作者：
DUDA, RO
中科院分区：
文献类型：
--
作者：
BABAUD, J;WITKIN, AP;DUDA, RO
尺度空间滤波通过将信号变换为与包含尺度或带宽参数的核卷积的原始信号的连续版本来构造分层符号信号描述。结果表明，高斯概率密度函数是唯一的内核在一个广泛的类，一阶最大值和最小值，分别增加和减少时，滤波器的带宽增加。这个结果的后果进行了探讨时，信号或其图像的线性微分算子进行分析，在尺度空间中的变换的过零轮廓。
Scale-space filtering constructs hierarchic symbolic signal descriptions by transforming the signal into a continuum of versions of the original signal convolved with a kernal containing a scale or bandwidth parameter. It is shown that the Gaussian probability density function is the only kernel in a broad class for which first-order maxima and minima, respectively, increase and decrease when the bandwidth of the filter is increased. The consequences of this result are explored when the signal-or its image by a linear differential operator-is analyzed in terms of zero-crossing contours of the transform in scale-space.