稳健性(进化)
高斯分布
人工智能
计算机科学
核(代数)
高斯滤波器
模式识别(心理学)
滤波器(信号处理)
直线(几何图形)
比例(比率)
高斯噪声
特征提取
特征(语言学)
计算机视觉
高斯函数
算法
数学
图像(数学)
地理
几何学
物理
生物化学
化学
地图学
语言学
哲学
量子力学
组合数学
基因
作者
Baptiste Magnier,Ghulam Sakhi Shokouh,Louis Berthier,Marcel Pie,A. G. Ruggiero
标识
DOI:10.1109/icassp49357.2023.10095570
摘要
Existing filtering techniques fail to precisely detect adjacent line features in multi-scale applications. In this paper, a new filter composed of a bi-Gaussian and a semi-Gaussian kernel is proposed, capable of highlighting complex linear structures such as ridges and valleys of different widths, with noise robustness. Experiments have been performed on a set of both synthetic and real images containing adjacent line features. The obtained results show the performance of the new technique in comparison to the main existing filtering methods.
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