热红外港口图像特征的评估器提取与选择Evaluator-based extraction and selection of thermal infrared harbor image features
马兰,陈筱勇,邓国臣
摘要(Abstract):
针对低对比度、条纹噪声、低空间分辨率等特点而导致的热红外图像识别效果不佳问题,提出了一种港口目标热红外遥感图像特征提取与选择方法,实现了一定情况下港口目标的高精度分类。采用纹理、几何等29个特征,通过评估器选择最佳特征组合,并根据识别精度选择最佳分类器,能生成热红外图像港口目标22个最佳分类特征,且具有一定的鲁棒性。经过参数优化后的libSVM(一种支持向量机)分类器分类精度较高;白天图像比夜间图像分类精度更高;像素值、灰度直方图相关的一维和二维统计特征、局部二进制模式特征、边缘方向直方图特征等与灰度和纹理相关的特征对港口目标热红外图像识别影响较大。
关键词(KeyWords): 特征提取;特征选择;热红外图像;港口目标;评估器;分类器;热红外遥感
基金项目(Foundation):
作者(Author): 马兰,陈筱勇,邓国臣
DOI: 10.16251/j.cnki.1009-2307.2017.05.015
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