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Nurollah Tatar Mohammad Saadatseresht Hossein Arefi Ahmad Hadavand 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2018,61(11):2787-2800
Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure. 相似文献
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以空间目标为研究对象,针对双基地雷达时间、空间及频率同步误差导致的逆合成孔径雷达图像散焦问题,提出基于离散多项式相位变换的自聚焦算法。算法首先将目标平动、转动及同步误差导致的相位项统一建模为高阶多项式,利用离散多项式相位变换方法估计高阶多项式系数并据此构建补偿相位项,完成高阶相位补偿。最后进行方位压缩得到高聚焦度的二维ISAR像。算法通过选取合适的延时参数及成像积累时间可得到高精度参数估计及相位补偿,理论分析和仿真校验了算法性能优于常用的非参数化自聚焦算法。 相似文献
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针对LT喷泉码在准单向链路、高差错、链路恶劣易中断的信道环境应用时出现的运算量大、译码时延长、编码效率较低等问题,文章提出使用基于数据分块的分组级短码长喷泉码方案。其思想是将短码长LT码方案和分组级LT码方案结合起来,并且在数据子块的度序列生成过程中加入度值检测机制。实验仿真结果表明:与已提出的LT码方案相比,该方案能够有效地降低译码开销、计算代价和译码时延,提高系统的最大传输效率。 相似文献
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Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms. 相似文献
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Ali G. Hafez Essam Ghamry 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2011
One of global processes in ionosphere–thermosphere–magnetosphere system is the geomagnetic storms. It is of great importance to develop an algorithm that auto-detects sudden commencement because it could be an indicator of onset of the geomagnetic storm. Automatic detection of geomagnetic sudden commencement is based on time–frequency clusters generated by spectrogram. Proposed algorithm is tested on data set collected from stations belong to the international real-time magnetic observatory network (INTERMAGNET). Maximum standard deviation of algorithm detection times is observed to be one minute of the corresponding arrival times published by National Geophysical Data Center (NGDC). 相似文献