提出新模型将图像分解为结构、纹理和噪声三部分，适合处理含噪图像。
Noisy image decomposition: a new structure, texture and noise model based on local adaptivity
- 基于局部自适应正则化，分离图像中的结构、纹理与噪声
- 在含噪图像上优于Aujol和Chambolle的最新方法
- 可应用于图像去噪与内容分析，适合有噪声的视觉任务
近年来，图像分解算法被提出用于将图像分为结构和纹理两部分。然而，这些方法不适用于含噪图像，因为噪声会污染纹理成分。本文提出一种新模型，通过局部正则化方案，将图像分解为结构、纹理和噪声三个部分。实验结果表明，该方法在含噪图像上的表现优于Aujol与Chambolle的近期工作。最后，我们还提出一个融合两者优势的新模型。
原文摘要 · Abstract (English)
These last few years, image decomposition algorithms have been proposed to split an image into two parts: the structures and the textures. These algorithms are not adapted to the case of noisy images because the textures are corrupted by noise. In this paper, we propose a new model which decomposes an image into three parts (structures, textures and noise) based on a local regularization scheme. We compare our results with the recent work of Aujol and Chambolle. We finish by giving another model which combines the advantages of the two previous ones.
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