图像修补是图像复原研究中的一个重要内容,目的是根据图像现有的信息自动恢复丢失的信息,它可以广泛应用于旧照片中丢失信息的恢复、视频文字去除以及视频错误隐藏等。提出一种新的基于户(z)-Laplace算子的CDD图像修补算法,利用户(z)-Laplace算子的非线性逐项异性扩散的性能填充受损区域,主要修补有划痕的旧照片和被文字覆盖的图像。新的模型在图像恢复的同时良好地保持了图像边缘,通过数值实验,对比以往的P—La—place算子的CDD图像模型,所提模型具有更好的图像恢复效果,明显减少了“阶梯状”效应。
Image inpainting is an important research topic in the area of image restoration; its obiective is to restore the lost information according to around image information, which can be widely used to restore old photo, remove text and conceal errors in videos. In the paper, a new image inpainting using CDD based on p(z) -Laplace is proposed. This algorithm mainly reverts cracks in photo-graphs and removes texts from photos, which makes full use of the nonlinear anisotropic diffusion of p(z)-Laplace operator to inpaint damaged images. The diffusion coefficients in the new model are self-adaptive for the detective of edges. Then we show numerical evidence of the power of resolution of these models with respect to p(z) -Laplace operator.