摘要
针对航空照片中自动目标识别的复杂性,该文提出了一种基于神经网络的自动目标识别算法,算法包括检测和虚警排除两个阶段。检测阶段是在整幅区域中进行快速搜寻,找出所有可能的目标;虚警排除阶段是对检测阶段得到的结果进行进一步的验证,在尽可能保留全部真目标的前提下,将伪目标排除。实验结果证明了算法的可行性。
Due to the complexity of automatic target recognition for aerial photo this paper describes an automatic target recognition algorithm based on neural network. It includes two stages, target detection and false-alarm rejection. The first stage operates on the entire image to detect potential targets quickly. The second stage attempts to reject false target-like objects while retaining as many targets as possible. The experimental results show the algorithm is feasible.
出处
《电子与信息学报》
EI
CSCD
北大核心
2001年第7期722-725,共4页
Journal of Electronics & Information Technology
基金
中国博士后科学基金
国防科技重点实验室基金