返回
Fast image segmentation based on multi-resolution analysis and wavelets
DOI:10.1016/S0167-8655(03)00160-0.png)
摘要
En 中文
An efficient algorithm for image segmentation based on a multi-re solution application of a wavelets transform and feature distribution is presented. The original feature space is transformed into a lower resolution with a wavelets transform to derive fast computation of the optimum threshold value in a feature space. Based on this lower resolution version of the given feature space, a single feature value or multiple feature values are determined as the optimum threshold values. The optimum feature values, which are in the lower resolution, are projected onto the original feature space. In this step a refinement procedure may be added to detect the optimum threshold value. Experimental results for the proposed algorithm indicate feasibility and reliability for fast image segmentation. (C) 2003 Elsevier B.V. All rights reserved.
Keyword:
multi-resolution analysis
image segmentation
wavelets transform
feature space
multi-threshold
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.6W
机构
暂无机构信息
引用论文
Shortcut Faults and Lateral Spreading Activated in a Pull-Apart Basin by the 2018 Palu Earthquake, Central Sulawesi, Indonesia2018年印度尼西亚中苏拉威西省帕卢地震触发的拉分盆地中的捷径断层和侧向扩展

