首页> 外文会议>Asia-Pacific Conference on Synthetic Aperture Radar >Fast calculation of Adaptive-Non-Negative-Eigenvalue-Decomposition employing particle swarm Optimization
【24h】

Fast calculation of Adaptive-Non-Negative-Eigenvalue-Decomposition employing particle swarm Optimization

机译:快速计算适应性 - 非负面特征值 - 分解采用粒子群优化

获取原文

摘要

This paper considers a fast calculation of adaptiven-on-negative eigenvalue-decomposition (ANNED). ANNED is one of useful polarimetric decomposition techniques and provides valuable information for remote sensing from measured covariance matrix. It has a disadvantage to take long time to estimate the decomposition parameters. To overcome this problem, the generalized eigenvalue problem has been applied. However, in practical use, more speed up is needed. In this paper, a particle swarm optimization (PSO) is applied to ANNED with the generalized eigenvalue problem. Thus, more fast calculation of ANNED is achieved and it is possible that POLSAR image with many pixels is analyzed.
机译:本文认为快速计算适应负负特征值 - 分解(ANNAIN)。 ANNAND是有用的偏振分解技术之一,提供了从测量的协方差矩阵遥感的有价值的信息。花费很长时间估计分解参数有缺点。为了克服这个问题,已经应用了广义的特征值问题。但是,在实际使用中,需要更快的加速。在本文中,粒子群优化(PSO)被占据了广义特征值问题的倒置。因此,实现了更快速的始终计算,并且可以分析具有许多像素的Polsar图像。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号