摘要
传统的灰度重心法是一种用于对称目标的亚像素定位算法,其计算精度不高而且抗噪声性能较差。提出一种隔离算法,将其边缘像素分离,然后对内部像素灰度进行均值化,从而有效抑制内部像素噪声。同时,利用数据误差理论对这种算法的误差进行分析。最后,通过基于大天区面积多目标光纤光谱天文望远镜(LAMOST)标定实验,验证了这种算法的正确性,并表明优化算法有较好的噪声抑制性能。
In view of the poor antinomies performance of traditional gray weighted centered algorithm, an optimized algorithm is proposed. Object region is partitioned into inner pixel region and edge pixel region, and all grey levels of the inner pixels are averaged to effectively restrain the noise of inner pixels. At the same time, the error of improved algorithm is analyzed with error theory. Finally based on LAMOST calibration experiments are conducted to prove the validity of the improved algorithm,and indicate that the improved algorithm has better antimonies Derformance.
出处
《现代制造工程》
CSCD
2008年第4期13-15,41,共4页
Modern Manufacturing Engineering
基金
国家九五大科学工程资助项目(98BJG001)
