High Dynamic Range Illumination and Volume Rendering

The dynamic range of an image is defined as the ratio between the brightest and the dimmest measurable light intensity. In traditional real-time graph-ics applications, the color and light intensities are represented as 24-bitRGB triplets with 8-bit fixed point precision for each primary color component.

This color representation is mainly motivated by the dynamic range and the color gamut of commercial CRT² display monitors. The limited 8-bit precision, however, turns out to be inadequate to describe light intensities

2CRT: cathode ray tube.

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in the real world. This can be easily verified if you use a digital camera with variable exposure time. If you are taking several images of a real scene with varying exposure, you will most likely notice that every image contains illumination details that cannot be found in the other images.

The goal of high dynamic range imaging (HDRI) [282] is to capture as much of the original light intensities of a scene as possible and store the result at floating-point precision. In practice, HDR images are either synthesized by physically based rendering algorithms or obtained by HDR photography [40], which is based on multiexposure image-capture tech-niques as mentioned above. But why should we capture more information that we are able to display on our monitor? The answer to this question is twofold. The first reason is that we want to mimic the capabilities of the human eye to adapt itself to different brightness levels by contracting and dilating the pupil. The second reason comes from physically based rendering and image-based lighting. The appearance of realistic materials with different reflective behavior is dominated by different portions of the dynamic range of light. Fully realistic lighting can only be achieved if all the subtleties caused by the entire dynamic range are considered.

One of the most popular applications of HDR images is image-based lighting as introduced by Paul Debevec [41]. A virtual scene is illuminated by images from the real world. The basic idea is essentially the same as reflection mapping described above, except for the high dynamic range.

The incident light from a real environment is captured by taking omnidi-rectional multiexposure photographs and reconstructing the incident light intensities (environment maps). Similar techniques can be used to derive HDR irradiance maps.

Tone-mapping techniques are used to map the high dynamic range back to the low dynamic range of conventional display monitors. Many tone-mapping techniques have been proposed in recent years [47]. Basically, they can be divided into global and local approaches. Global tone map-ping approaches calculate a spatially uniform scaling function to map the high dynamic range to 8-bitRGB. These approaches are based on the total brightness of an image. Local tone mapping operators only consider the light intensities in a limited neighborhood of each pixel. The scaling func-tion is spatially varying and parts of the image with different brightness levels are handled separately.

In recent years, many rendering methods have incorporated formats of a higher dynamic range for representing illumination or colors. High dynamic range techniques require all rendering operations to be performed at floating-point precision. In response to this requirement, current GPU architectures support texture formats and render targets with 16-bit and 32-bit floating-point precision for each primary color component.

Apart from external illumination with HDR environment, the idea of treating volumes as light-emitting entities makes a high dynamic range

5.9 Further Reading 137

Figure 5.8.Examples of a high dynamic range volume-rendering system. Turbulent mixing of air and sulfur hexafluoride (SF₆). The small images are generated at dif-ferent exposure levels. (Images courtesy of Xiaoru Yuan, Minh X. Nguyen, Baoquan Chen, and David Porter, University of Minnesota at Twin Cities. Data provided by David Porter and Paul Woodward, Lab of Computer Science and Computer Engi-neering (LCSE), University of Minnesota at Twin Cities ( c2005 IEEE).)

approach very attractive. High dynamic range volume rendering re-quires floating-point render targets as well as alpha blending and transfer functions in floating-point precision. High-precision alpha blending with floating-point render targets is discussed in Section 9.5. Appropriate trans-fer functions are implemented using floating-point texture formats for the dependent texture look-ups. Finally, tone mapping operators must be ap-plied to map the pixel values from the floating-point render target to the visible frame buffer with the usual 24-bitRGBAformat. Yuan et al. demon-strate a working implementation of a HDR volume rendering system [307].

They propose effective methods and user interfaces for specifying HDR transfer functions. An adaptive logarithmic mapping function is used for tone reproduction. Example images produced by their implementation are displayed in Figure 5.8. Another volume-rendering framework that sup-ports high dynamic range rendering was presented by Vollrath et al. [275].

5.9 Further Reading

Although most of the local illumination techniques described in this chap-ter violate the laws of physics in one way or the other, they significantly

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138 Local Volume Illumination

contribute to the comprehensibility and the visual quality of the image re-sults. Global illumination techniques will be discussed in the next chapter.

Optimization strategies such as deferred shading is explained in Chap-ter 8. Non-photorealistic approaches to volume illumination are discussed in Chapter 14.

For further reference on accurate illumination, Glassner has written a very detailed and comprehensive book on the theory of physically based illumination in two volumes [80]. A more practical text on illumination and rendering techniques is Physically Based Rendering by Pharr and Humphries [211]. The book Real-Time Shadingby Olano et al. is an ex-cellent introduction to physically accurate illumination and programmable shading for real-time applications.

For more information on high dynamic range imaging and image-based lighting, we refer to the comprehensive guide by Reinhard et al. [221].

There also exist several SIGGRAPH course notes on image-based lighting that can be used as reference [281].

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