Cited By
View all- Tang RChen LZou YLai ZAlbertini MYang X(2021)Lightweight network with one-shot aggregation for image super-resolutionJournal of Real-Time Image Processing10.1007/s11554-021-01127-618:4(1275-1284)Online publication date: 1-Aug-2021
GPU-parallel interpolation using the edge-direction based normal vector method for terrain triangular mesh
Pages 813 - 822
Abstract
In the geographic information field, triangular mesh modes are often used to describe terrain, where the normal vector to the surface at the node of a triangular mesh plays an important role in reconstruction and display. However, the normal vectors on the nodes of triangular meshes cannot be given directly, but instead must be computed using known data. Currently, the most common method of computing the normal vector at the nodes on a triangular mesh is to sum the normal vectors of the adjacent triangular facets using various weighting factors. For complex terrain surfaces, such a method is not very effective, and in some cases is not as good as classical weighted average algorithms. By studying interpolation based on edge-direction, combined with a terrain triangular mesh, we propose using a GPU-Parallel normal vector interpolation meth od based on the edge-direction for a terrain triangular mesh. Since terrain data is usually large, traditional serial algorithms are difficult to use while still meeting real-time requirements. In this paper, we use CUDA optimization strategies to make full use of the GPU (NVIDIA TESLA K80) for effectively solving this problem. The experimental results show that compared to traditional weighted average algorithms, the accuracy of the normal vector to the surface at the node increases significantly, and compared to serial algorithms only on CPU, speeds are increased by 646.4 times with the I/O transfer time being taken into account, meeting the real-time requirements.
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Published: 01 April 2018
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View all- Tang RChen LZou YLai ZAlbertini MYang X(2021)Lightweight network with one-shot aggregation for image super-resolutionJournal of Real-Time Image Processing10.1007/s11554-021-01127-618:4(1275-1284)Online publication date: 1-Aug-2021