CAJ | 학술논문

针对Harris检测出的角点位置会发生偏移和易产生伪角点,以及在角点匹配过程中计算复杂,容易产生误匹配等缺点,该文提出了基于良分布的亚像素定位角点的图像配准方法.该方法首先使用多尺度Harris算子检测图像的角点作为初始兴趣点,并采用自适应非极大值抑制对兴趣点的数量进行限制,以减少后续过程的计算复杂度,提高算法效率,同时使得角点在图像中处于良分布状态.然后利用亚像素定位技术进行精确定位,排除伪角点和不稳定的角点.最后使用随机抽样一致性算法对初始匹配进行鲁棒的模型参数估计.实验结果表明算法配准效率改进明显,并具有良好的精确性和鲁棒性.
침대Harris검측출적각점위치회발생편이화역산생위각점,이급재각점필배과정중계산복잡,용역산생오필배등결점,해문제출료기우량분포적아상소정위각점적도상배준방법.해방법수선사용다척도Harris산자검측도상적각점작위초시흥취점,병채용자괄응비겁대치억제대흥취점적수량진행한제,이감소후속과정적계산복잡도,제고산법효솔,동시사득각점재도상중처우량분포상태.연후이용아상소정위기술진행정학정위,배제위각점화불은정적각점.최후사용수궤추양일치성산법대초시필배진행로봉적모형삼수고계.실험결과표명산법배준효솔개진명현,병구유량호적정학성화로봉성.
To deal with the false and unstable corners, high computational complexity and incorrect matching, a new image registration algorithm is proposed based on corners which are well-distributed in image and with sub-pixel localization precision. Firstly corners in an image are detected by multi-scale Harris operator, which are taken as initial interest points. And then adaptive non-maximal suppression is used to limit the number of interest points, so the computational complexity is decreased and the efficiency of the algorithm is improved. At the mean time, the corners are made to be well-distributed in image. Since the location of initial Harris corners have offset and false corners have existed, sub-pixel localization technique is applied to determine the location of corners and eliminate the false and unstable corners in this process. Finally, RANSAC is used to estimate the parameters robustly based on initial matching. Experiments showed that the proposed algorithm has a good performance of efficiency, accuracy and robustness.