ABSTRACT

Line integral convolution is a technique originally developed for visualizing vector fields, such as wind or water directions, that places densely packed lines following the direction of movement. Geisthövel and Hurni adapted line integral convolution to terrain generalization in 2018. Their method successfully removes details and retains sharp mountain ridges; it is particularly suited for creating generalized shaded relief. This paper extends line integral convolution generalization with a series of enhancements to reduce spurious artifacts, accentuate mountain ridges, control the level of detail in mountain slopes, and preserve sharp transitions to flat areas. The enhanced line integral convolution generalization effectively removes excessive terrain details without changing the position of terrain features. Sharp mountain ridgelines are accentuated, and transitions to flat waterbodies and valley bottoms are preserved. Shaded relief imagery derived from generalized elevation models is visually pleasing and resembles manually produced shaded relief.

摘要

线积分卷积是一种最初用于可视化矢量场（例如风向或水向）的技术，该矢量场沿着运动方向放置密集的线。Geisthövel和Hurni在2018年将线积分卷积应用于地形综合。他们的方法成功去除了细节并保留了陡峭的山脊；它特别适合于创建广义的阴影浮雕。本文通过一系列增强功能扩展了线积分卷积泛化，以减少伪造的伪像，加深山脊，控制山坡上的细节水平并保持向平坦区域的清晰过渡。增强的线积分卷积一般化有效地去除了过多的地形细节，而无需更改地形特征的位置。陡峭的山脊线突出，保留了向平坦水体和山谷底部的过渡。从广义立面模型得出的阴影浮雕图像在视觉上令人愉悦，类似于手动生成的阴影浮雕。