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Layered Light Field Reconstruction for Defocus Blur

机译:散焦模糊的分层光场重建

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We present a novel algorithm for reconstructing high-quality defocus blur from a sparsely sampled light field. Our algorithm builds upon recent developments in the area of sheared reconstruction filters and significantly improves reconstruction quality and performance. While previous filtering techniques can be ineffective in regions with complex occlusion, our algorithm handles such scenarios well by partitioning the input samples into depth layers. These depth layers are filtered independently and then combined together, taking into account inter-layer visibility. We also introduce a new separable formulation of sheared reconstruction filters that achieves real-time preformance on a modern GPU and is more than two orders of magnitude faster than previously published techniques.
机译:我们提出了一种新算法,用于从稀疏采样的光场中重建高质量的散焦模糊。我们的算法建立在剪切重建滤波器领域的最新发展基础上,可显着提高重建质量和性能。尽管先前的过滤技术在具有复杂遮挡的区域中可能无效,但我们的算法通过将输入样本划分为深度层来很好地处理此类情况。考虑到层间可见性,对这些深度层进行独立过滤,然后组合在一起。我们还介绍了一种新的可剪切重构滤波器的可分离公式,该公式可在现代GPU上实现实时性能,并且比以前发布的技术快两个数量级。

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