基于奇异性检测的信号去噪新方法

Denoising by Singularity Detection

该文引进了一种基于奇异性检测的信号去噪方法,并对其在二维降噪中所需进行的复杂的线性内插作了进一步简化,使得整个二维降噪得以大大简化而达到快速运算和节省存储量的目的。文中详细描述了该算法的理论基础并给出其一维计算机仿真,同时也给出了进一步简化后的二维降噪仿真。这种去噪方法不需要信号或噪声的先验信息。仿真结果表明,相比其它小波去噪方法,该方法的主要优势在于:它在某一时刻的脉冲噪声的辨识和去除能力相当强,而且在去噪的同时能很好地保持信号边缘。

A signal denoising algorithm based on singularity detection is introduced in this paper. It simplified the complicated linear interpolation operation needed in the 2-D image denoising so that the 2-D denoising is greatly simplified and it can also get the fast denoising and save lots of memory. A complete description of this method and its 1-D denoising simulation are presented. A simplified 2-D denoising simulation is presented, too. This method does not need the prior information of signal or noise. Simulation results indicate that compared to other wavelet based denoising algorithms, the main advantage of this method is: it can better detect and reduce the pulse noise and it can reduce the noise while keeping the signal edges better.