Modeling occlusion and scaling in natural images
Modeling occlusion and scaling in natural images
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DOI：
10.1137/060659041
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发表时间：
2007-01-01
影响因子：
1.6
通讯作者：
Roueff, Francois
中科院分区：
文献类型：
--
作者：
Gousseau, Yann;Roueff, Francois
枯叶模型由数学形态学学派引入，由随机闭集（对象）的叠加组成，使人们能够对遮挡现象进行建模。当结合特定的大小分布的对象，一个获得的随机场提供足够的自然图像模型。然而，这个框架对对象的大小施加了限制。我们考虑这些随机场的极限时，让截断大小趋于零和无穷大。其结果是，我们得到一个随机场，其中包含均匀的区域，满足缩放特性，是统计相关的自然图像建模。然后，我们调查这些功能的图像的正则性的框架中的Besov空间的综合效果。
The dead leaves model, introduced by the mathematical morphology school, consists of the superposition of random closed sets (the objects) and enables one to model the occlusion phenomena. When combined with specific size distributions for objects, one obtains random fields providing adequate models for natural images. However, this framework imposes bounds on the sizes of objects. We consider the limits of these random fields when letting the cutoff sizes tend to zero and infinity. As a result we obtain a random field that contains homogeneous regions, satisfies scaling properties, and is statistically relevant for modeling natural images. We then investigate the combined effect of these features on the regularity of images in the framework of Besov spaces.