基于拉普拉斯金字塔分解的多尺度边缘检测
Multiscale edge detection based on Laplacian pyramid
董鸿燕 1王磊 1李吉成 1沈振康1
作者信息
- 1. 国防科技大学,ATR重点实验室,湖南,长沙,410073
- 折叠
摘要
边缘表现为图像中具有奇异性点的集合,利用改进的拉普拉斯金字塔分解捕获这些奇异性点,得到各尺度下的带通图像,通过分析,得出分解后的带通图像在边缘处产生零交叉点,构造统计量帮助提取零交叉点,再通过多尺度边缘融合实现多尺度边缘提取.与LOG和Canny边缘检测的对比实验表明,所建立的算法能够可靠、有效、精确的获得图像的边缘.
Abstract
Edge is characterized as the singularity points in the image. Laplacian Pyramid (LP) decomposition was used to capture the point singularities to obtain the multiscale band-pass images. Then it was analyzed that the obtained band-pass images was characterized as zerocrossing at the edges. A zerocrossing detection algorithm assisted by computing a statistic and a multiscale edge synthesizing algorithm were proposed to implement multiscale edge detection. Compared with the edge detectors of LOG (Laplacian of Gaussian) and Canny,the algorithm can detect edges of images more reliably and effectively.
关键词
奇异性/边缘检测/拉普拉斯金字塔/多尺度Key words
singularity/edge detection/Laplacian pyramid/multiscale引用本文复制引用
基金项目
武器装备预研基金(51483020105ZS9309)
出版年
2007
NETL
NSTL
维普
万方数据