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An RBF-based compression method for image-based relighting

机译:基于RBF的基于图像的补光压缩方法

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In image-based relighting, a pixel is associated with a number of sampled radiance values. This paper presents a two-level compression method. In the first level, the plenoptic property of a pixel is approximated by a spherical radial basis function (SRBF) network. That means that the spherical plenoptic function of each pixel is represented by a number of SRBF weights. In the second level, we apply a wavelet-based method to compress these SRBF weights. To reduce the visual artifact due to quantization noise, we develop a constrained method for estimating the SRBF weights. Our proposed approach is superior to JPEG, JPEG2000, and MPEG. Compared with the spherical harmonics approach, our approach has a lower complexity, while the visual quality is comparable. The real-time rendering method for our SRBF representation is also discussed.
机译:在基于图像的重新照明中,像素与多个采样的辐射值关联。本文提出了一种两级压缩方法。在第一级中,像素的全光特性通过球形径向基函数(SRBF)网络近似。这意味着每个像素的球面全光功能由多个SRBF权重表示。在第二级中,我们应用基于小波的方法来压缩这些SRBF权重。为了减少归因于量化噪声的视觉伪像,我们开发了一种用于估计SRBF权重的约束方法。我们提出的方法优于JPEG,JPEG2000和MPEG。与球形谐波方法相比,我们的方法具有较低的复杂度,而视觉质量却相当。还讨论了用于SRBF表示的实时渲染方法。

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