SAR图像车辆目标二重方差间隙度特征及其鉴别  

The Duplicate Variance Lacunarity Feature of Vehicle Targets in SAR Imagery and the Discriminating

作　　者：黄凯[1] 李禹[1] 粟毅[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073

出　　处：《信息工程期刊（中英文版）》2014年第3期104-110,共7页Scientific Journal of Information Engineering

基　　金：受国家自然科学基金项目支持资助（基金号：61171135）.

摘　　要：在对间隙度特征及多尺度间隙度特征存在问题分析的基础之上，提出二重方差间隙度特征。利用差分盒维法提取该特征时，将盒子质量定义为盒子内像素幅度值的方差，再用盒子质量的方差与其均值平方之比加上l得到二重方差问隙度。运用大量SAR图像ROI切片鉴别特征统计分析实验，及对整幅场景SAR图像目标鉴别结果对比分析实验，证明本文所提二重方差间隙度特征对SAR图像车辆目标的鉴别性能明显提高。A duplicate variance lacunarity feature was proposed by analyzing the issue of lacunarity and multi-scale lacunarity features. The box mass is defined as the intensity variance of pixels locating in the box when obtaining this feature by DBC （Differential Box Counting）. Then we add the ratio of the boxes mass variance to their square mean with 1 and get the duplicate variance lacunarity. The experiments on this discriminating feature using a large number of SAR imagery ROIs （Region of Interest） and target discrimination of large SAR scene are carried out to demonstrate the outstanding capability of the duplicate variance lacunarity in discriminating the vehicle targets in SAR imagery.

关 键 词：SAR 目标鉴别 分形 二重方差间隙度 

分 类 号：TP[自动化与计算机技术]