Concurrent edge/region detection from a Peano scan

G. Seetharaman, S. Bouchafa, B. Zavidovique
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Abstract

This paper deals with an adaptive sub-sampling process that is an example of a more general class of data processing. Our approach consists of spanning a Z-tree over the image. The Z-tree is the bin-tree built from the 1D pixel sequence obtained through a peculiar scan called the Peano traversal. A conditional rotation operator, defined to manipulate the Z-tree, supports the Peano scan adaption. Iterating rotations before tree inversion allows us to rebuild various mosaic versions of a same initial image. In the application outlined here, a fair stress is put on the way spatial redundancies are highlighted by this image shuffling process. This helps in constructing various versions from the initial data where both edges are simultaneously detected.
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从皮亚诺扫描并发边缘/区域检测
本文讨论了一种自适应子采样过程,它是一类更一般的数据处理的一个例子。我们的方法包括在图像上生成z树。z树是通过一种称为Peano遍历的特殊扫描获得的1D像素序列构建的bin树。为操作z树而定义的条件旋转操作符支持Peano扫描自适应。在树反演之前的迭代旋转允许我们重建相同初始图像的各种马赛克版本。在这里概述的应用程序中,通过图像变换过程强调空间冗余的方式。这有助于从同时检测两个边缘的初始数据构建各种版本。
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