采用非线性方向导数的混合噪声鲁棒角点检测算法

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采用非线性方向导数的混合噪声鲁棒角点检测算法

更新时间：2025-07-09

- 采用非线性方向导数的混合噪声鲁棒角点检测算法
- Issue 11, Pages: 115-124(2021)
- 作者机构：
  
  西安邮电大学通信与信息工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Published：2021
- 稿件说明：
移动端阅览
[J]. 2021, (11): 115-124.
DOI：

[J]. 2021, (11): 115-124. DOI：

摘要

为提高角点特征检测准确率

针对混合噪声下特征提取不准确而容易产生伪角点的问题

提出了一种基于非线性方向导数(NDD)的角点检测算法。利用Canny算法提取原始图像的边缘轮廓;分别构建各向同性和各向异性高斯方向导数滤波器的空域双窗

对每个边缘像素计算基于直方图分层技术的快速非线性方向导数特征;量化方向生成K个离散方向滤波器

根据响应向量最大值确定主方向;将3个尺度下非线性导数的比率值融合为新角点测度;进行阈值和非极大值抑制获得最终角点检测结果。在角点检测图像数据集上

分别针对高斯噪声、椒盐噪声和高斯椒盐混合噪声干扰图像

利用不同算法获取配准角点和错误角点数

并进行不同图像变换下的平均重复率实验。实验结果表明:在椒盐噪声和混合噪声下

所提算法的角点检测精度和平均重复率均优于其他角点检测算法的;对于方差为15的高斯噪声和密度为5%的椒盐噪声的混合噪声干扰图像

所提算法比CSS、CPDA、ANDD、Gabor和MDRR算法的平均检测准确率分别高5.4%、13.1%、11.6%、9%和7.3%

而平均错检率分别低86.9%、86%、86.5%、83.7%和83.9%

综合性能均优于对比算法。

Abstract

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references

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