XU Chen,KANG Xue,YANG Ling.Multi-temporal Cloud Removal based on Particle Swarm K-means Clustering Algorithm[J].Journal of Chengdu University of Information Technology,2020,35(04):424-429.[doi:10.16836/j.cnki.jcuit.2020.04.010]
基于粒子群K均值聚类算法的多时相去云处理
- Title:
- Multi-temporal Cloud Removal based on Particle Swarm K-means Clustering Algorithm
- 文章编号:
- 2096-1618(2020)04-0424-06
- Keywords:
- cloud removal algorithm; particle swarm; K-means clustering
- 分类号:
- TP311
- 文献标志码:
- A
- 摘要:
- 如何有效地减少或去除云的影响,不仅可以提高遥感数据的利用率,同时也是遥感数据进行准确解译的重要途径。将粒子群算法和K均值算法有效结合,提出一种改进的多时相去云方法。该算法有效克服了K均值算法容易陷入局部极值的缺点,结合粒子群算法反复迭代寻求全局最优解。实验结果表明,该算法收敛速度快,效果具有全局优化的特征,为研究去云算法提供一种简单有效的方法
- Abstract:
- How to reduce or remove the influence of clouds effectively can not only improve the utilization of remote sensing data, but also an important way for interpretation of remote sensing data accurately. The paper considers the problem of clouds covering area acquired at different dates, by using an improved K-means clustering based on particle swarm optimization algorithm(K-M PSO)to remove or reduce cloud disturbance.This algorithm overcomes the shortcoming of traditional K-means clustering algorithm easily involving into the local optima, searches for optimization solutions based on the iterative particle swarm optimization method. The results shows that K-M PSO algorithm not only improves the convergence rate, but also optimized all area, it provides a simple and effective method to study the cloud removal algorithm
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备注/Memo
收稿日期:2019-12-27
基金项目:山东省自然科学基金资助项目(ZR2017MD001)