CAJ | 학술논문

多变量乘积模型在极化合成孔径雷达(Polarimetric Synthetic Aperture Radar,PolSAR)图像建模领域中应用广泛,其纹理分量统计模型的选择直接影响到拟合的准确性。针对多变量乘积模型纹理分量分布的选择问题,提出了一种基于矩阵对数累积量(Matrix Log-Cumulant,MLC)的 PolSAR 图像统计模型无监督辨识方法。该方法首先将二阶和三阶 MLC平面进行着色,然后将 PolSAR数据投射到该平面上,根据像素点所在区域的颜色来辨识其对应的统计分布模型。新方法的优点是对全图中各区域的统计模型有简洁、宏观的辨识结果,能为后续的分类识别和目标检测等图像解译手段提供重要支撑。最后,用仿真数据和实测数据对该方法进行了分析。实验结果表明,该方法能实现对图像中不同区域分布模型的有效辨识。
다변량승적모형재겁화합성공경뢰체(Polarimetric Synthetic Aperture Radar,PolSAR)도상건모영역중응용엄범,기문리분량통계모형적선택직접영향도의합적준학성。침대다변량승적모형문리분량분포적선택문제,제출료일충기우구진대수루적량(Matrix Log-Cumulant,MLC)적 PolSAR 도상통계모형무감독변식방법。해방법수선장이계화삼계 MLC평면진행착색,연후장 PolSAR수거투사도해평면상,근거상소점소재구역적안색래변식기대응적통계분포모형。신방법적우점시대전도중각구역적통계모형유간길、굉관적변식결과,능위후속적분류식별화목표검측등도상해역수단제공중요지탱。최후,용방진수거화실측수거대해방법진행료분석。실험결과표명,해방법능실현대도상중불동구역분포모형적유효변식。
The multi-variant product model is widely applied in the field of PolSAR imagery,whose selection of texture component directly affects the modelwhose accuracy.Aimed at the problem of statistical model recognition for the texture component,an unsupervised method based on covariance matrix log-cumulants (MLC) is proposed.This method colors the second and third MLCs plane,then the PolSAR data are proj ected on the plane,and the statistical model is distinguished by the color of the pixels.The main advantage of the new method is to give a simple and macroscopic result,which can provide important support for the subsequent target detection,identification and classification of PolSAR data.Finally, experiments on the new method are made using simulated data and real PolSAR data and the results show that the new estimator is effective and robust.