改进的简单线性迭代聚类超像素

Kwang-Shik Kim, Dongni Zhang, Mun-Cheon Kang, S. Ko
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引用次数: 38

摘要

超像素是图像中不包含边缘的小区域。在所有的超像素算法中,简单线性迭代聚类(SLIC)方法因其实用性而被广泛采用。然而,产生的超像素有时不能很好地附着在边缘上。在本文中,我们提出了一种改进的SLIC超像素方法来解决这个问题。实验表明,与传统方法相比,该方法在不显著增加处理时间的情况下产生了边界与图像边缘更贴合的超像素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved simple linear iterative clustering superpixels
The superpixels are small regions in an image which do not contain edges inside. Among all the superpixel algorithms, the simple linear iterative clustering (SLIC) method is widely adopted due to its practicality. However, the resultant superpixels sometimes do not well adhere to the edges. In this paper, we present an improved SLIC superpixel method to solve this problem. Experiments show that the proposed method produces superpixels whose boundaries better adhere to the image edges without significantly increasing the processing time compared with the conventional method.
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