摘要
针对高分辨率可见光图像中靠岸舰船的灰度特征和纹理特征与港口设施极为相似而难以自动检测的问题,提出了一种利用邻域自相似局部特征提取算子提取港口舰船局部显著性特征,经过特征空间分析,并利用先验知识信息,自动检测港口舰船的算法和处理流程。实验结果表明,该处理方法具有较好的可操作性和鲁棒性,能够快速准确地检测出港口舰船目标。
In high-resolution remote sensing images the gray- scale and texture features, of the ships docking in harbor area, are similar to that of the coast, so it is difficult to automatically detect them. A automatic ship detection method, which is based on a neighborhood self-similarity local salient feature extractor and further space analysis,combined with the utility of prior information, is presented. Experiments show that this method can detect ships in the harbor area accurately and efficiently, and is of high practicability and robustness.
出处
《中国图象图形学报》
CSCD
北大核心
2009年第4期591-597,共7页
Journal of Image and Graphics
关键词
高分辨率遥感图像
邻域自相似局部特征
特征空间分析
先验信息
high-resolution remote sensing images, neighborhood self-similarity local feature, feature space analysis, prior information
作者简介
胡俊华（1980-），男。中国科学技术大学电子工程与信息科学系博士研究生。研究方向为图像处理、模式识别、遥感图像目标识别等。E-mail：icefox@mail．ustc．edu．cn
