遥感图像上颜色增强旋转不变霍夫森林目标检测方法的并行计算研究

项目名称： 遥感图像上颜色增强旋转不变霍夫森林目标检测方法的并行计算研究

项目编号： No.41201450

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 地理学

项目作者： 雷震

作者单位： 武汉大学

项目金额： 25万元

中文摘要： 颜色增强旋转不变霍夫森林方法（CRIHF）适合于遥感图像目标检测，具有稳健、有效、通用性好的特点，然而此方法还存在检测速度慢，以及由此带来的高耗时特性较难研究、较难在工程应用中推广的问题。随着半导体技术发展到接近原子尺度，计算硬件需采用并行结构继续发展。并行计算因其优良的可扩展性以及充分利用并行计算硬件的能力可以大幅提高科学计算速度，正在成为科学计算的主流趋势。本项目顺应这一潮流，研究CRIHF方法并行计算的内在模型和外在应用，主要研究内容包括：（1）CRIHF方法在多种并行架构下的并行计算模型及其工程实现，（2）以卫星数据处理和无人机在航目标检测为应用场景验证方法，并总结重要参数对准确度、速度的影响规律。（3）在并行计算的支持下研究方法的高耗时特性扩展。通过本项目的研究，可以解决CRIHF方法的上述难题，扩展方法的应用范围，为快速遥感图像目标检测提供新方法。

中文关键词： 遥感数据处理；随机森林；并行化；；

英文摘要： Color-enhanced Rotation-Invariant Hough Forest (CRIHF) is a stable, efficient and versatile object detection method for remotely sensed imagery. However it is often forbiddingly slow to be successfully applied in many practical applications. Meanwhile, with the development of semi-conductor technology down to the atomic level, further development of computing hardware has required the use of parallel infra-structure. This new trend of development has often rendered algorithmic design a bottleneck as most complex algorithms are traditionally designed for the sequential computer model. Historically, parallel computation has been used to significantly improve the speed of certain scientific computation problems such as matrix computation and scientific simulations due to their structural regularity and excellent scalability. However, designing efficient algorithms for more complex problems to better utilize parallel hardware has been always a key research question in scientific computation and it is becoming important due to the wide-spread use of parallel hardware. Following such tendency, this project proposes to study the method and application of combining parallel computation and the CRIHF method. The main research contents include: (1) Design of a parallel computation model of the CRIHF method and its impleme

英文关键词： remote sensing；random forest；parallalization；；