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   bubble函数 在 电信技术 分类中 的翻译结果: 查询用时:0.057秒
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相关语句
  bubble function
    Lateral inhibition described by Bubble function is a very common mechanism in living creature vision information processing system.
    侧抑制是生物视觉信息处理中广泛存在的一种机制,Bubble函数很好刻画了侧抑制现象。
短句来源
    In this paper,we use Bubble function as wavelet base and Gaussian function as smooth function to decompose signal using Mallat algorithm and the position of maximum decomposition value is just the position of edges. This algorithm has different ability to reduce noise and to extract edges according to different scales of Bubble function. When the scale of Bubble function is growing wide,then the ability of reducing noise increases and the ability of extracting detail edges decreases;
    本文利用Bubble函数构成小波,高斯函数作为平滑函数,用Mallat快速算法进行小波分解,分解的局部极大值就是多尺度边缘,理论和实验都表明,这种算法对于不同的尺度,有不同的抑制噪声的能力和提取边缘细节的能力,当Bubble函数的尺度较大时,抑制噪声的能力增强,提取边缘细节的能力变差;
短句来源
    Bubble function is a band pass filter in the frequency domains, while it doesn't have the ability to adjust bandwidth of filter. Therefor an improved bubble function was proposed, it can get different time-frequency domain response and filtering effect through adjusting parameter.
    针对bubble函数不具有调节带宽的缺点,提出了一种改进的bubble函数,该改进函数能够通过调节参数来获取不同时域、频域响应和滤波效果。
短句来源
    And the improved bubble function was combined with stationary wavelet to get multiresolution network. Using improved bubble function to enhance the contrast and stationary wavelet to reduce the noise, the edge can be distilled with lower noise exactly、effectively and quickly.
    将改进后的bubble函数与平稳小波相结合构造出多分辨率网络,该网络利用平稳小波变换去除噪声、利用改进bubble函数增强图像边缘,从而可以准确、有效、快速的提取出图像的边缘。
短句来源
    The developed algorithm is verified better than the traditional bubble function.
    实验结果表明,该方法优于传统bubble函数与平稳小波相结合提取边缘的效果。
短句来源
  bubble function
    Lateral inhibition described by Bubble function is a very common mechanism in living creature vision information processing system.
    侧抑制是生物视觉信息处理中广泛存在的一种机制,Bubble函数很好刻画了侧抑制现象。
短句来源
    In this paper,we use Bubble function as wavelet base and Gaussian function as smooth function to decompose signal using Mallat algorithm and the position of maximum decomposition value is just the position of edges. This algorithm has different ability to reduce noise and to extract edges according to different scales of Bubble function. When the scale of Bubble function is growing wide,then the ability of reducing noise increases and the ability of extracting detail edges decreases;
    本文利用Bubble函数构成小波,高斯函数作为平滑函数,用Mallat快速算法进行小波分解,分解的局部极大值就是多尺度边缘,理论和实验都表明,这种算法对于不同的尺度,有不同的抑制噪声的能力和提取边缘细节的能力,当Bubble函数的尺度较大时,抑制噪声的能力增强,提取边缘细节的能力变差;
短句来源
    Bubble function is a band pass filter in the frequency domains, while it doesn't have the ability to adjust bandwidth of filter. Therefor an improved bubble function was proposed, it can get different time-frequency domain response and filtering effect through adjusting parameter.
    针对bubble函数不具有调节带宽的缺点,提出了一种改进的bubble函数,该改进函数能够通过调节参数来获取不同时域、频域响应和滤波效果。
短句来源
    And the improved bubble function was combined with stationary wavelet to get multiresolution network. Using improved bubble function to enhance the contrast and stationary wavelet to reduce the noise, the edge can be distilled with lower noise exactly、effectively and quickly.
    将改进后的bubble函数与平稳小波相结合构造出多分辨率网络,该网络利用平稳小波变换去除噪声、利用改进bubble函数增强图像边缘,从而可以准确、有效、快速的提取出图像的边缘。
短句来源
    The developed algorithm is verified better than the traditional bubble function.
    实验结果表明,该方法优于传统bubble函数与平稳小波相结合提取边缘的效果。
短句来源
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Lateral inhibition described by Bubble function is a very common mechanism in living creature vision information processing system.In this paper,we use Bubble function as wavelet base and Gaussian function as smooth function to decompose signal using Mallat algorithm and the position of maximum decomposition value is just the position of edges.This algorithm has different ability to reduce noise and to extract edges according to different scales of Bubble function.When the scale of Bubble function is growing...

Lateral inhibition described by Bubble function is a very common mechanism in living creature vision information processing system.In this paper,we use Bubble function as wavelet base and Gaussian function as smooth function to decompose signal using Mallat algorithm and the position of maximum decomposition value is just the position of edges.This algorithm has different ability to reduce noise and to extract edges according to different scales of Bubble function.When the scale of Bubble function is growing wide,then the ability of reducing noise increases and the ability of extracting detail edges decreases;otherwise,the ability of reducing noise decreases and the ability of extracting detail edge increases. Both the theory and experiment manifest that this algorithm is very efficient and practical.

侧抑制是生物视觉信息处理中广泛存在的一种机制,Bubble函数很好刻画了侧抑制现象。本文利用Bubble函数构成小波,高斯函数作为平滑函数,用Mallat快速算法进行小波分解,分解的局部极大值就是多尺度边缘,理论和实验都表明,这种算法对于不同的尺度,有不同的抑制噪声的能力和提取边缘细节的能力,当Bubble函数的尺度较大时,抑制噪声的能力增强,提取边缘细节的能力变差;当Bubble函数的尺度较小时,抑制噪声的能力变弱,提取边缘细节的能力增强

Bubble function is a band pass filter in the frequency domains, while it doesn't have the ability to adjust bandwidth of filter. Therefor an improved bubble function was proposed, it can get different time-frequency domain response and filtering effect through adjusting parameter. And the improved bubble function was combined with stationary wavelet to get multiresolution network. Using improved bubble function to enhance the contrast and stationary wavelet to reduce the noise, the edge can be distilled with...

Bubble function is a band pass filter in the frequency domains, while it doesn't have the ability to adjust bandwidth of filter. Therefor an improved bubble function was proposed, it can get different time-frequency domain response and filtering effect through adjusting parameter. And the improved bubble function was combined with stationary wavelet to get multiresolution network. Using improved bubble function to enhance the contrast and stationary wavelet to reduce the noise, the edge can be distilled with lower noise exactly、effectively and quickly. The developed algorithm is verified better than the traditional bubble function.

针对bubble函数不具有调节带宽的缺点,提出了一种改进的bubble函数,该改进函数能够通过调节参数来获取不同时域、频域响应和滤波效果。将改进后的bubble函数与平稳小波相结合构造出多分辨率网络,该网络利用平稳小波变换去除噪声、利用改进bubble函数增强图像边缘,从而可以准确、有效、快速的提取出图像的边缘。实验结果表明,该方法优于传统bubble函数与平稳小波相结合提取边缘的效果。

 
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