基于核各向异性扩散的低信噪比裂纹降噪算法研究

Research of Low Signal-to-Noise Ratio Crack Noise Reduction Based on Kernel Anisotropic Diffusion

利用各向异性扩散和核方法,提出了一种新的核各向异性扩散去噪算法,应用于跨座式单轨轨道梁面线性裂纹的去噪取得了较好效果。在各向异性扩散的基础上,增加一个边缘增强算子,用于增强微弱的裂纹边缘信息,并且根据噪声均匀分布在多维空间的特点,把低维数据推广到高维空间,结合核方法的优点,在核空间中实现去噪,同时采用平均绝对差值的自动扩散终止规则也提高了核各向异性扩散的效率。选用不同的边缘增强权值,讨论了合适的权值范围。该方法应用于低信噪比的轨道梁面线性裂纹宽度为0.4 mm噪声的去除时,与中值滤波、传统P-M各向异性扩散去噪相比,该方法去噪效果以及信噪比明显优于其它去噪算法。

A new kernel anisotropic diffusion noise removal algorithm is proposed, mrougn amsotroplc diffusion and kernel method, to denoise linear crack on the light rail beam surface, and preferable results are obtained. On the basis of anisotropic diffusion, an enhancement operator which promotes the weak crack edge is added, and according to the characteristics of noise uniformly distributing in the multi-dimensional space, the low-dimensional data is promoted to high-dimensional space. Except for denoising in the kernel space, average absolute difference value of automatic diffusion termination criterion is introduced to enhance the efficiency of diffusion. A different edge enhanced weight is choosed to discuss the appropriate weight range. This method has been applied to noise removal of low signal-to-noise ratio track surface beam linear crack of 0. 4 mm width. Compared with median filter and traditional P-M anisotropic diffusion, the kernel anisotropic diffusion outperforms them for denoised result and signal- to-noise ratio.