基于数据重组算法的目标提取方法

图像分割实现目标与背景分离后,需要定位目标并提取其特征.传统像素标记方法易出现重复标记与判断现象,效率非常低.本文提出了一种"数据重组"(DRG)算法用于目标的提取,利用为重兵器靶场试验搭建的空中测试平台上的传感器采集的地面红外图像序列,实现了地面控制点在图像中的实时检测和提取.DRG算法只对目标图像扫描一次仅提取与目标有关的有效数据,将图像问题转化为简单的数据结构问题,降低了问题的复杂度,无需繁琐的标记处理,没有重复性问题,而且简单、实现方便.结果表明,算法对目标的定位具有一定的准确性和可靠性,具有相当的抗干扰与抗噪声能力,并适合于具连通性的各类形状和走小的目标的提取.

Target Extraction Based on Data Regrouping Algorithm

It's an important work to detect and locate targets in image.A new method,named Dam Regrouping (DRG) algorithm,is proposed.This approach scans the image only once to record data related to tatgets,and transforms image process problem to data structure problem,thus complexity is reduced.The DRG method doesn't need overlaborate labeling and has nothing with repetitiveness.Using the infrared images of ground gathered by the sensor of our airborne testing system for heavy-weapon range test,we apply DRG algorithm to extract infrared small targets and achieve the goal of detecting and locating ground control points in real time.The experiment result shows that our method is accurate,reliable,and has great ability of anti-jamming and anti-noise.