High Dynamic Range for High Fidelity Image Synthesis of Real Scenes

高动态范围，用于真实场景的高保真图像合成

• 批准号: EP/D032148/1
• 负责人: Alan Chalmers
• 金额: $ 41.3万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FD032148%2F1
• 关键词: Dynamic; Range; Fidelity; Image; Synthesis

The computer graphics industry, and in particular those involved with films, games, simulation, virtual reality and military applications, continue to demand more realistic computer-generated images, that is computed images that more accurately match the real scene they are intended to represent. This is particularly challenging when considering images of the natural world, which presents our visual system with a wide range of colours and intensities. In most real scenes, for example, looking from inside a house towards a window, the ratio between the darkest areas (e.g. inside the room) and the brightest area (outside the window), the so-called contrast ratio, could be many thousands to one. A typical computer monitor only has a contrast ratio of about 100:1 and is thus incapable of accurately displaying such scenes.A number of appearance-preserving, or tone-mapping, operators (TMOs) have been developed in order to try achieve a perceptual match between the real-world scene and what is displayed on the computer monitor. However, it has not yet been possible to validate the fidelity of these TMOs thoroughly against the real scenes they are trying to portray. The recent development of novel, high dynamic range (HDR) displays, capable of 75,000:1 contrast ratio now provide the opportunity to compute and display computer-generated images that are perceptually much closer to the real world.This research proposal will use these novel HDR displays to evaluate existing TMOs to see how well they do preserve the appearance of the real scenes, and will use the insights gained to develop new, more accurate TMOs for existing computer monitors and HDR displays. A framework will also be produced that will provide a straightforward, objective way of comparing real and synthetic images. Two applications, which are critically dependent on the realism of computed images, are virtual archaeology and military simulations. When investigating past environments on a computer, failure to produce images that accurately match what the past environment may have looked like, may in fact lead to the archaeologists misinterpreting the past. Similarly, the incorrect display of a military vehicle attempting to camouflage in a certain terrain may lead to detection of the vehicle in the real battlefield scenario. We will use specific examples from archaeology and camouflage to test the results of our research.

计算机图形工业，特别是那些涉及电影、游戏、模拟、虚拟现实和军事应用的计算机图形工业，继续需要更逼真的计算机生成图像，即更精确地匹配它们打算表示的真实的场景的计算图像。当考虑自然世界的图像时，这尤其具有挑战性，自然世界为我们的视觉系统提供了广泛的颜色和强度。在大多数真实的场景中，例如，从房子内部向窗户看，最暗的区域（例如，房间内部）和最亮的区域（窗户外部）之间的比率（所谓的对比度）可以是数千比一。典型的计算机监视器仅具有大约100：1的对比度，因此不能准确地显示这样的场景。已经开发了许多外观保持或色调映射算子（TMO），以便尝试实现真实世界场景与计算机监视器上显示的内容之间的感知匹配。然而，还不可能根据这些TMO试图描绘的真实的场景来彻底验证它们的保真度。最近开发的新型高动态范围（HDR）显示器能够达到75，000：1的对比度，现在提供了计算和显示计算机生成的图像的机会，这些图像在感知上更接近真实的世界。本研究提案将使用这些新型HDR显示器来评估现有的TMO，以了解它们在多大程度上保留了真实的场景的外观，并将使用所获得的见解来开发用于现有计算机监视器和HDR显示器的新的、更精确的TMO。一个框架也将产生，将提供一个直接的，客观的方式比较真实的和合成图像。两个应用，这是严重依赖于计算图像的真实性，是虚拟考古学和军事模拟。当在计算机上调查过去的环境时，无法产生与过去环境可能的样子准确匹配的图像，实际上可能导致考古学家误解过去。类似地，试图在特定地形中伪装的军用车辆的不正确显示可能导致在真实的战场场景中检测到车辆。我们将使用考古学和伪装学的具体例子来测试我们的研究结果。

项目成果

Advanced High Dynamic Range Imaging

• DOI: 10.1201/9781315119526
• 发表时间: 2017-07
• 作者: F. Banterle;A. Artusi;Kurt Debattista;A. Chalmers

A framework for inverse tone mapping

• DOI: 10.1007/s00371-007-0124-9
• 发表时间: 2007-05
• 期刊: The Visual Computer
• 作者: F. Banterle;P. Ledda;Kurt Debattista;A. Chalmers;Marina Bloj

High Dynamic Range Imaging and LDR Expansion for Generating HDR Content

用于生成 HDR 内容的高动态范围成像和 LDR 扩展

• 发表时间: 2009
• 作者: F Banterle

Enabling stereoscopic high dynamic range video

• DOI: 10.1016/j.image.2013.08.004
• 发表时间: 2014-02
• 期刊: Signal Process. Image Commun.
• 作者: Elmedin Selmanovic;Kurt Debattista;Thomas Bashford-Rogers;A. Chalmers

A GPU-friendly method for high dynamic range texture compression using inverse tone mapping

• DOI: 10.1145/1375714.1375722
• 发表时间: 2008-05
• 作者: F. Banterle;Kurt Debattista;P. Ledda;A. Chalmers