论文部分内容阅读
结合放射性能谱的统计特性,提出了一种基于高斯尺度空间的平滑滤波方法.构造由高斯函数构成的尺度空间,将能谱在该空间内进行多次投影,并在投影中调整高斯函数的权重以实现能谱平滑滤波.选取的标准方差σ和尺度j较小时(如σ=0.2~0.6,j=0),每次平滑后峰形畸变小,适于对弱峰的平滑;选取σ和j较大时(如σ=0.6~1.0,j=1,2,3),可使统计涨落得到较大抑制,并使谱峰成形加快,适于统计涨落较大且谱峰较明显的能谱平滑.结果表明,该方法可灵活地选择标准方差σ和尺度空间Vj,以适应平滑精度和处理速度的要求,且计算简便,是一种性能良好的平滑滤波方法.
Combining with the statistical properties of the radioactive spectrum, a new smoothing filtering method based on Gaussian scale space is proposed. The scale space composed of Gaussian function is constructed, the energy spectrum is projected multiple times in the space and the Gaussian function is adjusted And the weight is used to realize the spectrum smoothing filtering.When the standard deviation σ and the scale j are small (such as σ = 0.2-0.6, j = 0), the peak shape distortion after each smoothing is small, which is suitable for the smoothing of the weak peak. When j is large (eg, σ = 0.6-1.0, j = 1,2,3), the statistical fluctuation can be greatly suppressed and the peak shape can be accelerated, which is suitable for the statistical fluctuation and the spectral peak to be larger The results show that this method can flexibly select the standard deviation σ and the scale space Vj to meet the requirements of smoothing accuracy and processing speed, and the calculation is simple and convenient. It is a good smoothing filtering method.