从多源图像建模详细的云场景

Yunchi Cen, Xiaohui Liang, Junping Chen, Bailin Yang, Frederick W. B. Li
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引用次数: 2

摘要

真实感云对于提高计算机图形应用程序(如飞行模拟)的质量至关重要。数据驱动方法是一种有效的云建模方法,但现有方法通常只利用一个数据源作为输入。例如,通常使用自然图像来模拟具有细节的小尺度云,而使用卫星图像和WRF数据来模拟没有细节的大尺度云。为了构建具有细节的大规模云场景,提出了一种从卫星和自然图像中提取相关云信息的新方法。实验表明,与现有方法相比,该方法可以生成更精细的云场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Detailed Cloud Scene from Multi-source Images
Realistic cloud is essential for enhancing the quality of computer graphics applications, such as flight simulation. Data-driven method is an effective way in cloud modeling, but existing methods typically only utilize one data source as input. For example, natural images are usually used to model small-scale cloud with details, and satellite images and WRF data are used to model large scale cloud without details. To construct large-scale cloud scene with details, we propose a novel method to extract relevant cloud information from both satellite and natural images. Experiments show our method can produce more detailed cloud scene comparing with existing methods.
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