通过图切割递归MDL:在分割中的应用

Lena Gorelick, Andrew Delong, O. Veksler, Yuri Boykov
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引用次数: 10

摘要

我们提出了一种新的基于补丁的图像表示,它很有用,因为它(1)在多个尺度上固有地检测具有重复结构的区域,(2)产生无参数的分层分割。我们通过将图像分解成连贯的区域来描述图像,其中每个区域通过使用一组简单变换重复实例化补丁来很好地描述(容易重建)。换句话说,一个好的片段是一个对某些模式有足够重复的片段,而一个补丁是有用的,如果它包含一个在图像中重复的模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recursive MDL via graph cuts: Application to segmentation
We propose a novel patch-based image representation that is useful because it (1) inherently detects regions with repetitive structure at multiple scales and (2) yields a parameterless hierarchical segmentation. We describe an image by breaking it into coherent regions where each region is well-described (easily reconstructed) by repeatedly instantiating a patch using a set of simple transformations. In other words, a good segment is one that has sufficient repetition of some pattern, and a patch is useful if it contains a pattern that is repeated in the image.
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