基于自适应噪声闭值的EMD域多尺度边缘提取

为了利用经验模式分解(EMD)方法对具有不同信噪比的信号提取边缘信息，提出一种采用中位数绝对离差方法来佑计噪声阂值的EMI)域多尺度边缘提取算法。该算法首先采用EMD方法求得各尺度残余分量的抖率信号;其次采用阂值化方法去除斜率信号中的噪声，其中噪声阈值采用中位数绝对离差方法求得;最后经空间一致性检验，输出信号的边缘信息。仿真实验结果显示，基于自适应噪声阂值的EMD域多尺度边缘提取可以准确提取信号边缘信息，同时抑制噪声信号。

Multi-scale Edge Detection in the EMD Domain Using the Adaptive Noise Threshold

A multi-scale edge detection in the EMD domain using the median absolute deviation to estimate the noise threshold was proposed to detect the edges of noisy signals with different signal to noise ratios. The new algorithm first calculates the slope of the EMD residuals in scales. Second, it eliminates the noise in the slope signal by thresholding, the noise threshold of which is estimated by the median absolute deviation. At last, it outputs the edge information by the spatial consistence test Simulation results show that, the multi-scale edge detection in the EMD domain using the adaptive noise threshold can accurately detect the edges of signals, and suppress the noise.