An iterative median filtering algorithm based on improved noise detection for the removal of impulse noises from the images is presented.
本文提出了一种基于噪声检测的迭代中值滤波算法。
On the basis of the results, an approach of improved median filtering is applied to selectively remove the impulse noises in a color image.
采用改进的自适应矢量中值滤波法，对脉冲噪声有选择地滤除。
It first detects impulse noises in an image in a serial mode, and the threshold, which is used to estimate noise pixel, can be modified adaptively.
该方法首先采用串行方式，对含有脉冲噪声的图像进行逐点检测，其中判断噪声点的阈值可自适应地调整。
Impulse noises are often encountered in image acquisition and communication. We present an impulse noise removal method using long range correlation.
针对图像采集与通信过程中经常遇到的脉冲噪声问题，提出基于远程相关性的脉冲噪声消除方法。
As a result, the experiment shows that the algorithm can effectively filter out Gaussian and impulse noises, as well as preserve more detailed information of the original image.
实验结果表明，与传统的中值滤波和均值滤波算法相比，该算法能够有效地去除高斯和脉冲噪声，同时能够保留更多的图像细节信息。
The method eliminates impulse noises by median filtering then extracts edges by Otsu's thresholding based on local entropy of image, connects discrete edges and detects objects regions.
该方法首先进行中值滤波消除图像脉冲噪声，然后计算图像局部熵进行阈值选择提取目标边缘，最后进行边缘连接分割出目标区域。
This method can effectively remove fixed noises of the Gaussian White noise and impulse noise.
该方法能够有效去除高斯白噪声和脉冲噪声的混合噪声。
However, in respect of a vibration acceleration signal, the signal to noise ratio (SNR) is often so small that the periodic impulse component is submersed in its intense background noises.
通常检测的机械振动加速度信号，由于信噪比太低，即使存在周期性的冲击分量也往往被淹没在强的背景噪声之中。
However, in respect of a vibration acceleration signal, the signal to noise ratio (SNR) is often so small that the periodic impulse component is submersed in its intense background noises.
通常检测的机械振动加速度信号，由于信噪比太低，即使存在周期性的冲击分量也往往被淹没在强的背景噪声之中。
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