提花织物纹理的Allen-Cahn水平集去噪方法

Image Denoising for Jacquard Fabrics Texture Based on Allen-Cahn Level Set Model

针对含噪织物纹理在去噪过程中存在的形状失真和拓扑演变适应性差的问题 ,提出一种新的提花织物纹理图像去噪算法 ,并讨论了Allen Cahn方程的水平集公式 该算法结合Allen Cahn方程和水平集去噪技术 ,首先利用Allen Cahn方程生成面积保留的平均曲率运动 ;然后利用水平集公式演化纹理图像中的曲线 ,该公式可以提供简单且稳健的边缘估计和阈值策略 实验结果表明了该算法的可行性 。

Deals with the problem of shape distortion and the poor adaptation to topological evolution in denoising of fabric textures under noisy environment. A novel noise removal algorithm for jacquard fabrics textures was proposed, and a level set formulation for the Allen-Cahn equation was discussed. The algorithm combined the merits of Allen-Cahn equation and level set denoising technology. First, the Allen-Cahn equation was put forward to generate area-preserving mean curvature motion. Then a level set formulation was developed to evolve curves arising in texture image. The proposed formulation also provided easier and more robust edge estimation and threshold strategies. Experimental results show that the proposed algorithm is feasible, and reaches an obvious effect in terms of edge-preserving image denoising.