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| 1 | 针对高光谱图像的目标分类方法现状与展望显示文摘进入21世纪,遥感技术成为一项非常重要的空间成像技术。高光谱图像分类是遥感技术应用中非常重要的一项研究内容,在民用和军用上都实现了应用。高光谱图像分类是通过给每个像元添加分类标签,最终达到区分地物并且识别目标的目的。本文简要阐述了高光谱图像的分类过程及其面临的主要问题;在总结前人研究的基础上归纳了4类主要的高光谱图像分类策略,简要分析了其优缺点及适用范围;分析了近年来出现的新型分类器及其优化方法。最后,对于高光谱图像分类研究存在的主要困难进行了总结,并对未来发展的方向进行了展望。 | 李秉璇 周冰 贺宣 刘贺雄 | 2020 | 激光与红外2020，50，3： | 16 |
| 2 | 小波包信息熵特征矢量光谱角高光谱影像分类显示文摘目的针对高光谱数据波段多、数据存在冗余的特点,将小波包信息熵特征引入到高光谱遥感分类中。方法通过对光谱曲线进行小波包分解变换,定义了小波包信息熵特征矢量光谱角分类方法(WPE-SAM),基于USGS光谱库中4种矿物光谱数据的分析表明,WPE-SAM可增大类间地物的可区分性。在特征矢量空间对Salina高光谱影像进行分类计算,并讨论了小波包最佳分解层的确定,分析了WPE-SAM与光谱角制图(SAM)方法的分类精度。结果 Salina数据实例计算表明:小波包信息熵矢量能较好地描述原始光谱特征,WPE-SAM分类方法可行,总体分类精度(OA)由SAM的78.62%提高到WPE-SAM的78.66%,Kappa系数由0.769 0增加到0.769 5,平均分类精度(AA)由83.14%提高到84.18%。此外,通过Pavia数据验证了WPE-SAM分类方法具有较强的普适性。结论小波包信息熵特征可较好地表示原始光谱波峰、波谷等特征信息,定义的小波包信息熵特征矢量光谱角分类方法(WPE-SAM)可增大类间地物可区分性,有利于分类。实验结果表明,WPE-SAM分类方法技术可行,总体精度及Kappa系数较SAM有一定的提高,且有较强的普适性。但WPE-SAM方法精度与效率有待进一步提高。 | 郭辉 杨可明 张文文 刘聪 夏天 | 2017 | 中国图象图形学报2017，22，2： | 4 |
| 3 | 基于随机森林的FY-2G云检测方法显示文摘根据遥感影像中云检测原理,提出了基于随机森林的遥感影像云检测方法,并将其应用于FY-2G影像。结合国家气象卫星中心(NSMC)的云检测产品数据进行了算法的精度检验,云检测个例的精度检验结果显,最高命中率(POD)为88.32%,最低误报率(FAR)为9.36%,临界成功指数(CSI)为80.14%。结果表明,该方法有效地提高了云检测精度,同时能正确标识NSMC中部分误判的情况。 | 付华联 冯杰 李军 刘军 | 2019 | 测绘通报2019，，3： | 4 |
| 4 | 基于乡镇尺度Landsat8 OLI影像融合算法适应性研究显示文摘本文利用OIF因子选择乡镇尺度下Landsat8 OLI影像MS最优波段组合,在此基础上,研究OLI影像MS波段与PAN波段对6种融合算法:Brovey法、PCA法、Daubechies小波变换法、Coifet小波变换法、HIS与小波相结合的变换法、PCA与小波相结合的变换法融合的适应性,并对融合前后影像进行SVM分类,以验证融合结果在实际生产应用中的有效性。结果表明:B456为7波段35种组合方式中最佳波段组合,其OIF值为27.842;对融合前后影像进行定性和定量精度评价,OLI影像对PCA算法融合适应性最强,各精度指标均占优;Daubechies小波算法光谱扭曲度最小;HIS-wavelet算法清晰度最高;PCA-wavelet算法相关系数最高,融合结果信息含量最大;适应性最差为Brovey算法。土地利用分类精度验证结果表明:OLI影像经PCA算法融合后有助于提高分类精度。 | 黄安 王旭红 杨联安 杜挺 王元元 刘建红 | 2015 | 山东农业大学学报(自然科学版)2015，46，4： | 4 |
| 5 | Tracking with nonlinear measurement model by coordinate rotation transformation显示文摘A new filtering method is proposed to accurately estimate target state via decreasing the nonlinearity between radar polar measurements(or spherical measurements in three-dimensional(3D) radar) and target position in Cartesian coordinate. The degree of linearity is quantified here by utilizing correlation coefficient and Taylor series expansion. With the proposed method, the original measurements are converted from polar or spherical coordinate to a carefully chosen Cartesian coordinate system that is obtained by coordinate rotation transformation to maximize the linearity degree of the conversion function from polar/spherical to Cartesian coordinate. Then the target state is filtered along each axis of the chosen Cartesian coordinate. This method is compared with extended Kalman filter(EKF), Converted Measurement Kalman filter(CMKF), unscented Kalman filter(UKF) as well as Decoupled Converted Measurement Kalman filter(DECMKF). This new method provides highly accurate position and velocity with consistent estimation. | ZENG Tao LI Chun Xia LIU Quan Hua CHEN Xin Liang | 2014 | Science China(Technological Sciences)2014，57，12： | 4 |
| 6 | The quantitative evaluation of application of hyperspectral data based on multi-parameters joint optimization显示文摘In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral. | LI Na HUANG Ping ZHAO HuiJie JIA GuoRui | 2014 | Science China(Technological Sciences)2014，57，11： | 1 |
| 7 | Accelerometer error estimation and compensation for three-axis gyro-stabilized camera mount based on proportional multiple-integral observer显示文摘This paper deals with the problem of accelerometer error estimation and compensation for a three-axis gyro-stabilized camera mount. In a dynamic environment, the aircraft motion acceleration affects the accelerometer output and causes a degradation of attitude steady accuracy. In order to improve control accuracy, this paper proposes a proportional multiple-integral observerbased control strategy to estimate and compensate the accelerometer error. The basic idea of this paper is to approximate the error property by using a q-order polynomial function and extend the error and its derivatives as augmented states. Then a proportional multiple-integral observer is developed to estimate the error, with which the relationship between the error and the imbalance torque is formulated. The estimated value is compared to an angle threshold, the result of which is used to compensate the accelerometer output. Through static and vehicle-mounted experiments, it is demonstrated that compared with the traditional method, the proposed method can improve the attitude steady accuracy effectively. | LI Shu Sheng ZHONG Mai Ying ZHAO Yan | 2014 | Science China(Technological Sciences)2014，57，12： | 1 |
| 8 | 智能交通背景下模糊聚类图像识别的优化设计显示文摘采用模糊聚类的遥感图像云识别聚类算法实现了多卫星云图识别改进设计,对于设计的模糊聚类算法,验证中表明算法的分类成功率较好,与其他算法相比其运行时间、准确度方面具有明显的优势,在多卫星云图识别的实验验证中得出,最终的实验测得的结果图可以有效地说明模糊聚类算法应用在遥感图像的云识别上的效果很好。实验结果对于多卫星复杂云图识别具有明显理论和实际应用价值。 | 苏红帆 | 2016 | 信息技术2016，40，12： | 1 |
| 9 | Fast nonnegative tensor ring decomposition based on the modulus method and low-rank approximation显示文摘Nonnegative tensor ring(NTR) decomposition is a powerful tool for capturing the significant features of tensor objects while preserving the multi-linear structure of tensor data. The existing algorithms rely on frequent reshaping and permutation operations in the optimization process and use a shrinking step size or projection techniques to ensure core tensor nonnegativity, which leads to a slow convergence rate, especially for large-scale problems. In this paper, we first propose an NTR algorithm based on the modulus method(NTR-MM), which constrains core tensor nonnegativity by modulus transformation. Second, a low-rank approximation(LRA) is introduced to NTR-MM(named LRA-NTR-MM), which not only reduces the computational complexity of NTR-MM significantly but also suppresses the noise. The simulation results demonstrate that the proposed LRA-NTR-MM algorithm achieves higher computational efficiency than the state-of-the-art algorithms while preserving the effectiveness of feature extraction. | YU YuYuan XIE Kan YU JinShi JIANG Qi XIE ShengLi | 2021 | Science China(Technological Sciences)2021，64，9： | 0 |
| 10 | Emergence of higher-level neuron properties using a hierarchical statistical distribution model显示文摘Essential to visual tasks such as object recognition is the formation of effective representations that generalize from specific instances of visual input. Neurons in primary visual cortex are typically hypothesized to efficiently encode image structures such as edge and textures from natural scenes. Here this paper proposed a novel hierarchical statistical distribution model to generalize higher-level neuron properties and encode distributed regularities that characterize local image regions. Two layers of our hierarchical model are presented to extract spiking activities of excitatory neurons decorrelated by inhibitory neurons and to construct the statistical patterns of input data, respectively. Trained on whitened natural images, parameters including neural connecting weights and distribution coding weights are estimated by their corresponding learning rules. To prove the feasibility and effectiveness of our model, several experiments on natural images are conducted. Adapting our model to natural scenes yields a distributed representation for higher-order statistical regularities. Comparison results provide insight into higher-level neurons which encode more abstract and invariant properties. | XIAN Ning DENG Yi Min DUAN HaiBin | 2019 | Science China(Technological Sciences)2019，62，4： | 0 |
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