【摘要】 首先从局部坐标角度分析整体变分(TV)模型与p-Laplace算子的物理意义,从本质上说明p-Laplace算子的扩散性能优于TV模型,进而提出一种基于p-Laplace算子的图像修补算法.该算法利用p-Laplace算子的非线性各向异性扩散的性能来填充受损区域.与TV修补算法相比,文中算法能快速收敛,并达到更好的修补效果,其综合性能优于TV修补算法.更多还原

【Abstract】 The physical characteristics of total variation(TV) model and p-Laplace operator in local coordinates are analyzed,which shows that the diffusion performance of p-Laplace operator is essentially superior to that of TV model.Then,an image inpainting algorithm based on p-Laplace operator is proposed. This algorithm makes full use of the nonlinear anisotropic diffusion of pLaplace operator to inpaint damaged images.Experimental results show that the proposed algorithm has better general performance in convergence speed and inpainting quality.更多还原