Adaptive Color Display via Perceptually-driven Factored Spectral Projection
Adaptive Color Display via Perceptually-driven Factored Spectral Projection
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DOI：
10.1145/2682631
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发表时间：
2015-11-01
影响因子：
6.2
通讯作者：
Wetzstein, Gordon
中科院分区：
文献类型：
--
作者：
Kauvar, Isaac;Yang, Samuel J.;Wetzstein, Gordon
傅立叶域中的稀疏性是一个重要的属性，它使得能够从一小组样本中密集地重建信号，例如4D光场。自然光谱的稀疏性通常来自连续参数，但重建算法通常在离散傅里叶域中工作。这些算法通常假设从连续原理导出的稀疏性在离散采样下也成立。这篇文章提出了一个重要的观察结果，即连续傅立叶谱中的稀疏性比离散谱中的稀疏性大得多。这种差异是由窗口效应造成的。当我们在一个有限的窗口上采样一个信号时，我们用一个无限sinc卷积它的频谱，这破坏了连续域中的大部分稀疏性。基于这一观察，我们提出了一种方法来重建，优化稀疏的连续傅立叶频谱。我们描述了我们的方法背后的理论，并讨论了它如何可以用来减少采样要求，提高重建质量。最后，我们展示了我们的方法的力量，通过展示它如何可以应用于从少量的1D视点轨迹恢复非朗伯光场的任务。基本的显示特性不断得到改善，特别是分辨率，动态范围和颜色再现。然而，尽管高分辨率和高动态范围显示器作为一种技术已经成熟，但是如何在不牺牲光吞吐量或进行其他权衡的情况下扩展显示器的色域仍然很不清楚。在本文中，我们提倡自适应彩色显示器，与硬件实现，允许颜色原色被动态选择，最佳色域和correspotnding像素状态可以计算在内容自适应和以用户为中心的方式。我们建立了一个灵活的色域投影仪，并开发了一个感知驱动的优化框架，强大的因素，一个广泛的色域目标图像到一组时间复用的原色和相应的像素值。我们表明，自适应初选有很多好处，固定色域选择，并表明我们的联合初选和色域映射算法比现有的方法表现更好。最后，我们评估所提出的计算显示系统广泛的模拟，并通过照片和用户实验，与原型自适应彩色投影仪。
Sparsity in the Fourier domain is an important property that enables the dense reconstruction of signals, such as 4D light fields, from a small set of samples. The sparsity of natural spectra is often derived from continuous arguments, but reconstruction algorithms typically work in the discrete Fourier domain. These algorithms usually assume that sparsity derived from continuous principles will hold under discrete sampling. This article makes the critical observation that sparsity is much greater in the continuous Fourier spectrum than in the discrete spectrum. This difference is caused by a windowing effect. When we sample a signal over a finite window, we convolve its spectrum by an infinite sinc, which destroys much of the sparsity that was in the continuous domain. Based on this observation, we propose an approach to reconstruction that optimizes for sparsity in the continuous Fourier spectrum. We describe the theory behind our approach and discuss how it can be used to reduce sampling requirements and improve reconstruction quality. Finally, we demonstrate the power of our approach by showing how it can be applied to the task of recovering non-Lambertian light fields from a small number of 1D viewpoint trajectories.Fundamental display characteristics are constantly being improved, especially resolution, dynamic range, and color reproduction. However, whereas high resolution and high-dynamic range displays have matured as a technology, it remains largely unclear how to extend the color gamut of a display without either sacrificing light throughput or making other tradeoffs. In this paper, we advocate for adaptive color display; with hardware implementations that allow for color primaries to be dynamically chosen, an optimal gamut and correspotnding pixel states can be computed in a content-adaptive and user-centric manner. We build a flexible gamut projector and develop a perceptually-driven optimization framework that robustly factors a wide color gamut target image into a set of time-multiplexed primaries and corresponding pixel values. We demonstrate that adaptive primary selection has many benefits over fixed gamut selection and show that our algorithm for joint primary selection and gamut mapping performs better than existing methods. Finally, we evaluate the proposed computational display system extensively in simulation and, via photographs and user experiments, with a prototype adaptive color projector.