基于阴影的HDR环境地图光检测

Andrew Chalmers, Taehyun Rhee
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摘要

高动态范围(HDR)环境地图(EMs)是包含HDR像素的球形纹理,用于照亮具有高真实感的虚拟场景。在EM中检测尽可能少的必要像素对于各种任务(如实时渲染和EM数据库管理)都很重要。为了解决这个问题,我们提出了一种基于阴影的算法来检测EM中最主要的光源。该算法考虑了纹理上半球内所有其他光源的相对影响。这是通过将EM分解为超像素来实现的,将超像素从最亮到最小排序,并使用0范数最小化来只保留必要的超像素,这些超像素可以保持EM的阴影质量,相对于可注意差异(JND)原则。我们表明,我们的方法改进了以前的方法,在检测尽可能少的光的同时仍然保留了em的阴影投射特性。
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Shadow-based Light Detection for HDR Environment Maps
High dynamic range (HDR) environment maps (EMs) are spherical textures containing HDR pixels used for illuminating virtual scenes with high realism. Detecting as few necessary pixels as possible within the EM is important for a variety of tasks, such as real-time rendering and EM database management. To address this, we propose a shadow-based algorithm for detecting the most dominant light sources within an EM. This algorithm takes into account the relative impact of all other light sources within the upper-hemisphere of the texture. This is achieved by decomposing an EM into superpixels, sorting the superpixels from brightest to least, and using ℓ0-norm minimisation to keep only the necessary superpixels that maintains the shadow quality of the EM with respect to the just noticeable difference (JND) principle. We show that our method improves upon prior methods in detecting as few lights as possible while still preserving the shadow-casting properties of EMs.
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