摘要
一种用于噪声图像边缘提取的算法首先对噪声图像进行小尺度高斯滤波,使用新型边缘检测算子获取引导信息(边缘检测算子在定位精度、抑制噪声和虚假边缘方面具有很好的性能),然后对各搜索轨迹进行分段自增强,最后根据自增强累积的程度获取噪声图像中的边缘。实验结果表明,该算法能够有效地从噪声图像中提取物体的真实边缘,并能最大限度地保留细节信息,性能优于经典的边缘提取算法。
Firstly, the noisy image is filtered by a small scale Gaussian Filter, then a new Large Template Edge Detector is designed in order to get more accurate lead information for the subsequential sub-edge self-reinforces,the edge detector has good performance on accurately locating, suppressing noise and fake edge. Finally, the real edge of noisy image is extracted from the accumulated search trajectories. Experimental results show that the proposed method can extract real edge in noisy image while keeping the image details and outperforms than the classical algorithm.
出处
《计算机应用研究》
CSCD
北大核心
2005年第8期235-237,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(60175001)
关键词
边缘提取
分段自增强
启发式搜索
小尺度高斯滤波
Edge Extraction
Sub-edge Accumulation
Heuristic Search
Small Scale Gaussian Filtering
