Visualisation of Earth Deformation in 2D

Nor Anita Fairos bt. Ismail, S. N. Kamarudin, M. Rahim, Jianguo Liu, P. Mason
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Abstract

The rapidly growing field of remote sensing is beginning to supply massive quantities of high-resolution imagery of the Earth and other planets. In the earth sciences, parallel supercomputers have always played a prominent role in the visualization of this imagery, and in other image processing applications designed to enhance and display the obtained information. Imageodesy is a technique for detection and measurement of feature shifts between two images based on local feature fitting algorithms such as Normalize Cross-Correlation (Crippen, 1992) and phase correlation. This technique allows the vast archives of optical imagery, collected by satellite systems such as SPOT and Landsat, to be used not only to detect but also to measure the subtle terrain displacements associated with earthquakes, glacial motion and volcanic processes, all to within sub-resolution accuracy and precision is also a major factor.
二维地球变形可视化
迅速发展的遥感领域开始提供大量的地球和其他行星的高分辨率图像。在地球科学中,并行超级计算机一直在这种图像的可视化和其他图像处理应用中发挥着突出的作用,这些应用旨在增强和显示所获得的信息。Imageodesy是一种基于局部特征拟合算法(如Normalize Cross-Correlation (Crippen, 1992)和相位相关)检测和测量两幅图像之间特征位移的技术。这项技术允许大量的光学图像档案,由卫星系统如SPOT和Landsat收集,不仅用于探测,而且还用于测量与地震、冰川运动和火山过程相关的细微地形位移,所有这些都在亚分辨率范围内精度和精度也是一个主要因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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