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The performances of the Laplacian of binomial distribution and the discrete Laplacian of Gaussian edge detection operators

机译:二项分布的拉普拉斯算子和高斯边缘检测算子的离散拉普拉斯算子的性能

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This paper presents a performance analysis and comparison between the Laplacian of binomial distribution (LOB) and the discrete Laplacian of Gaussian (DLOG) edge detection operators in the space domain and frequency domain. When the scale space constants of the two edge detection operators are large enough, the characteristics in space domain and frequency domain and performances in image detection are almost the same. But when the scale space constants are smaller, the conclusion can be made that the performances of the LOB operator are little better than that of the discrete LOG operator after comparisons of central frequency, 3 dB bandwidth and high frequency attenuation rate at cut off frequency in the frequency domain. The LOB operator may be considered as a discrete realization of LOG operator. Results of experiments are given to verify the correctness of analysis.
机译:本文在空间域和频域上,对二项分布的拉普拉斯算子(LOB)和高斯离散的拉普拉斯算子(DLOG)边缘检测算子进行了性能分析和比较。当两个边缘检测算子的尺度空间常数足够大时,空间域和频域的特性以及图像检测的性能几乎相同。但是,当尺度空间常数较小时,通过比较中心频率,3 dB带宽和截止频率下的高频衰减率,可以得出LOB运算符的性能略好于离散LOG运算符的性能。频域。 LOB运算符可以视为LOG运算符的离散实现。给出实验结果以验证分析的正确性。

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