无需参数的多尺度纹理分离，可精准提取特定类纹理。
Multiscale texture separation
- 结合小波-帕利滤波器与图像分解模型，实现纹理分离。
- 理论证明可近乎完美提取特定类纹理，实验验证有效。
- 扩展为方向性多尺度算法，适合真实与合成图像处理。
本文从理论上研究了Meyer图像卡通+纹理分解模型的行为。主要成果是提出一个新定理，表明通过结合该分解模型与合适的Littlewood-Paley滤波器，可近乎完美地提取某一类纹理。基于此定理，我们构建了一种无参数的多尺度纹理分离算法。进一步，通过设计方向性Littlewood-Paley滤波器组，将该算法拓展为方向性多尺度纹理分离方法。多项实验表明，该方法在合成图像和真实图像上均表现出高效性。
原文摘要 · Abstract (English)
In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images.
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