ID 原文 译文
13054 分析结果表明，目标的交叉极化分量与极化测量雷达系统的极化隔离度处在相同水平时，目标的交叉极化分量测量结果会明显偏离其真值，通过极化隔离度优于测量系统隔离度无源或有源极化定标体对系统进行标校可以减小系统极化隔离度带来的测量误差。 The analytcal results show that the measurng value of the target cross polarization is different fromits true value apparenty when the target cross-poarization approximatey equas the polarimetric isoation of the system.The measuring deviation caused by the system poarimetric isoation can be reduced by passive or act i ve polarimetric calibration object whose polarimetric isolation i s better than that of the radar system.
13055 本文工作为极化定标体的研制和全极化测量雷达的系统标校奠定了基础。 All these works wll l lay foundatons for the design and preparation of the polari-metc calibraton object, and also the calibraton of the fully polar metric radar.
13056 Marino于2012年提出了一种极化凹口滤波器(polarimetric notch filter, PNF/」,引起了业界内的广泛关注，但至今尚未查询到公开文献将其与极化合成孔径雷达(polarimetric synthetic aperture ra， dar, PolSAR)图像目标恒虚警率(constant false alarm rate, CFAR)检测领域内著名的极化白化滤波器(po- larimetric whitening filter, PWF)进行比较。 A new ship detector known as the polarimetrc notch fllter (PNF) was developed in 2012 by Marino"1#. No open iiteratures are found to compare the PNF with the classic polarimetric whitening fllter (PWF). The probability density functons (PDF) , the probability of false alarm (PFA) and the thresholds of the PWF detector are derived in closed forms in the inverse gamma-distributed textura! product model case (G0-Wishart). The detection performances of the PNF are compared with those of the classic PWF via simulated data and real data from AIRSAR in Wishart case and G0-Wishart case.
13057 最后利用仿真数据和来自AIRSAR的实测数据对PNF与PWF的性能进行了比较，结果表明一般情况下PWF的整体检测效能优于PNF，而PNF对不同统计模型的适应性优于PWF，在高海况情形下的检测性能比PWF要好。 The results show that the performance of the PWF in ship detection is better than that of the PNF in most cases, while the adaptability of PNF is better than that of the PWF in high sea state case.
13058 超像素分割在图像分割领域以其优异的性能表现被广泛应用!准确性和高效性是评价分割性能的重要指标。 Superpixel segmentaton has been widely used in the field of image segmentaton due to its excellent performance.
13059 简单线性迭代聚类(simple linear iterative clustering, SLIC)方法在光学图像上表现出了优异的性能，在极化合成孔径雷达(synthetc aperture radar, SAR)图像中也被广泛应用，然而/LIC方法中的 初始化步骤不能准确地定位类中心，需要多次的迭代纠正误差。 The simple lmear iterative clustering (SLIC) method shows excellent performance in optical images and has been widely used in polarimetric SAR i mages. However, the initialiation step of the SLIC method cannot accurately locate the class center, requiring multiple iterations to correct the errors.
13060 改进的分水岭方法(spatial constrained watershed, SCoW)是一种基于梯度阈值区分的简单且高效的分割方法，但是不能直接用于极化/AR图像。 The improved watershed method (SCoW) Es a sEmple and effcent segmentaton method based on gradient thresholding discrimination, but it cannot be drectly used in polarzing SAR images.
13061 本文受SCoW的启发,提出一种对SLIC进行预处理的分割方法，通过横虚警(constant false alarm rate, CFAR)边缘检测器计算得到极化SAR图像的梯度信息，并将梯度信息用于初始化分割。 Inspired by SCoW, in this paper, we propose a segmentation method which serves for the SLIC preprocessing step. First the edge information is detected by a CFAR edge detector, and then the edge information is used to initiate the segmentaton.
13062 基于两幅实测极化 SAR图像，将本文提出方法与其他三种方法对比。 Experiments using real PolSAR data show that this method can reduce the number of iterations.
13063 实验表明本文方法可以减少整个算法的迭代次数，得到更加符合图像信息、贴合图像边界的分割结果。 The segmentation result is more consistent with the image boundaries in comparison with other three superpxel segmentaton algorithms.