4D压缩和重照明与高分辨率光传输矩阵

Ewen Cheslack-Postava, N. Goodnight, Ren Ng, R. Ramamoorthi, G. Humphreys
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引用次数: 7

摘要

本文提出了一种利用高分辨率、预先计算的光传输矩阵进行有效压缩和重光照的方法。我们使用一个四维小波变换来实现这一点,变换传输矩阵的列,除了在以前的工作中使用的二维行变换。我们展示了一个标准的四维小波变换实际上可以膨胀矩阵的一部分,因为高频光导致高频图像不容易被压缩。因此,我们提出了一种自适应四维小波变换,它在避免膨胀和最大化矩阵数据稀疏性的水平上终止。最后,我们提出了一种自适应压缩传输矩阵的快速重照明算法。结合基于gpu的预计算管道,这导致图像和几何重光照系统的性能明显优于2D压缩技术,在存储成本和渲染速度方面平均提高2 -3倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
4D compression and relighting with high-resolution light transport matrices
This paper presents a method for efficient compression and relighting with high-resolution, precomputed light transport matrices. We accomplish this using a 4D wavelet transform, transforming the columns of the transport matrix, in addition to the 2D row transform used in previous work. We show that a standard 4D wavelet transform can actually inflate portions of the matrix, because high-frequency lights lead to high-frequency images that cannot easily be compressed. Therefore, we present an adaptive 4D wavelet transform that terminates at a level that avoids inflation and maximizes sparsity in the matrix data. Finally, we present an algorithm for fast relighting from adaptively compressed transport matrices. Combined with a GPU-based precomputation pipeline, this results in an image and geometry relighting system that performs significantly better than 2D compression techniques, on average 2x-3x better in terms of storage cost and rendering speed for equal quality matrices.
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