Following the advances in remote sensing technology in the last decade, the horizontal and vertical scan resolutions for digital terrains have reached the order of a meter and decimeter, respectively. At these resolut...
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ISBN:
(纸本)9781479914203
Following the advances in remote sensing technology in the last decade, the horizontal and vertical scan resolutions for digital terrains have reached the order of a meter and decimeter, respectively. At these resolutions, descriptions of real terrains require very large storage spaces. Efficient storage, transfer, retrieval, and manipulation of such large amounts of data require an efficient compression method. This paper presents a method for fast lossy and lossless compression of regular height fields, which are a commonly used solution for representing surfaces scanned at regular intervals along two axes. The method is suitable for SIMD parallel implementation and thus inherently suitable for modern gpu architectures, which significantly outperform modern CPUs in computation speed, and are already present in home computers. The method allows independent decompression of individual data points, as well as progressive decompression. Even in the case of lossy decompression, the decompressed surface is inherently seamless. The method's efficiency was confirmed through a CUDA implementation of compression and decompression algorithms, and application in a terrain visualization system.
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