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摘要: 本文研究如何利用不完整的小波系数来恢复原始图像. Chan, Shen 和 Zhou 已经提出了一种基于整体变分 (total variational, TV) 模型的小波域图像修补算法. TV 模型的主要优点是可以保持图像的边缘, 但该模型在平滑区容易产生阶梯效应, 使图像的修补效果不是很理想. 为了克服这个缺陷, 本文首先从局部坐标角度分析了TV模型与p-Laplace算子的物理意义, 从本质上说明了 p-Laplace 算子的扩散性能优于 TV 模型.然后给出了一种基于 p-Laplace 算子的小波域图像修补模型. 该模型不仅有效降低 TV 模型引入的阶梯效应, 而且能保持图像的边缘, 用较少的运算量得到比 TV 模型更好的修补效果. 实验结果表明, 该模型在运算时间和修补效果上都具有更好的综合性能.
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关键词:
- 图像修补 /
- 小波变换 /
- p-Laplace 算子 /
- 整体变分模型
Abstract: The problem of filling in missing or damaged wavelet coefficients is considered in this paper. Chan, Shen, and Zhou have proposed two total variation (TV) wavelet inpainting models to solve this problem. The main benefit of TV model is that it can keep the edges very well, but this method suffers from the staircase effect. To overcome this defect, we analyze the physical characteristics of TV model and p-Laplace operator in local coordinates, and explain that diffusion performance of $p$-Laplace is superior to that of TV model in essence. Afterwards, an inpainting model based on p-Laplace operator for damaged wavelet coefficients is presented. This new model can effectively reduce the staircase effect in TV model whereas it can still keep sharp edges as well as TV model. Experiment results show that better inpaingting quality can be achieved with much less computing time with our model.-
Key words:
- Image inpainting /
- wavelet transform /
- p-Laplace operator /
- total variation model
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