摘要
为解决Harris角点检测算法在多尺度条件下无法正确提取角点的问题,本文将经验模式分解(EMD)方法运用到二维图像特征点提取中。先利用二维EMD方法将图像分解到多个图像细节层,并定义为本征模函数(IMF),再利用Harris算子对各图像细节层进行角点检测,最后采用层层筛选的方法提取角点。对比实验结果表明,新算法得到的角点更加丰富,抗噪性增强,明显提高了图像角点检测性能。
To solve the problem of the Harris comer detection algorithm which cannot detect comers in multi-scales, this paper applies the Empirical Mode Decomposition （EMD） to comer detection of two-dimensional images. First, the image is decomposed into some image detail layers （Intrinsic Mode Functions, IMF） by the EMD, then use Harris corner detection operator on the details of the layer. Finally, filter the comer points layer by layer. The contrast experimental results show that, the new algorithm gets more comers, enhances the noise immunity and improves the image comer detection performance significantly
出处
《光电工程》
CAS
CSCD
北大核心
2012年第7期38-42,共5页
Opto-Electronic Engineering
基金
国家自然科学基金资助项目(61070104)
解放军理工大学工程兵学院基金资助项目
