Course Description
Current display devices can display only a limited range of contrast and colors, which is one of the main reasons that most image acquisition, processing, and display techniques use no more than eight bits per color channel. This course outlines recent advances in high-dynamic-range imaging, from capture to display, that remove this restriction, thereby enabling images to represent the color gamut and dynamic range of the original scene rather than the limited subspace imposed by current monitor technology. This hands-on course teaches how high-dynamic-range images can be captured, the file formats available to store them, and the algorithms required to prepare them for display on low-dynamic-range display devices. The trade-offs at each stage, from capture to display, are assessed, allowing attendees to make informed choices about data-capture techniques, file formats, and tone-reproduction operators. The course also covers recent advances in image-based lighting, in which HDR images can be used to illuminate CG objects and realistically integrate them into real-world scenes. Through practical examples taken from photography and the film industry, it shows the vast improvements in image fidelity afforded by high-dynamic-range imaging.
Prerequisites
Familiarity with basic techniques in digital photography, traditional eight-bit image editing, and basic computer graphics modeling and rendering. Also, familiarity with a specific image-editing package or 3D modeling and rendering package is helpful.
Intended Audience
Students, researchers, and industrial developers in digital photography, computer graphics rendering, real-time photoreal graphics, and visual effects production (especially rendering and compositing).
Additional Resources for the SIGGRAPH 2004 Course:
Course Syllabus:
- Introduction and Overview (Reinhard)
(8:30 - 8:40)
- Taking High Dynamic Range images (Debevec)
(8:40 - 9:20)
- Dynamic range in the real world
- Taking images with varying exposure - shutter, f/stop, ND filters
- Deriving the response curve
- Producing the radiance map
- Viewing and editing HDR imagery
- Capturing omnidirectional HDR images
- Acquiring a light probe image using a mirrored ball
- Fisheye and Panoramic camera techniques
- Indirect capture of HDR intensities
- Direct HDR Capture of the Sun and Sky
- HDR Image Post-Processing (Vigneting, glare and motion blur...)
- HDR Is as Easy as 1-2-3 (Ward)
(9:20 - 10:00)
- Easy capture of HDR Images
- Automatic exposure bracketing
- Hand-held image alignment
- Lens flare reduction and ghost removal
- HDR Image File formats
- Manufacturer's raw formats
- RADIANCE .pic/.hdr
- LogLuv Tiff .tif
- ILM's OpenEXR .exr
- Emerging formats
- Emerging High Dynamic Range Display Technologies
10:00-10:15 Break
- The Human Visual System and HDR Tone Mapping (Pattanaik)
(10:15 - 10:50)
- Human Visual System (HVS) Physiology
- HVS Sensitivity
- Models of Visual Adaptation
- Background Luminance in Images
- Tone Reproduction Operator Design
- Tone Reproduction Operators (Reinhard)
(10:50 - 11:25)
- Global operators
- Local operators
- Perceptually-inspired operators
- Engineering-based solutions
- Current state-of-the-art
- HDR Image Based Lighting (Debevec)
(11:25 - 12:05)
- Illuminating synthetic objects with real light
- IBL using a global illumination renderer
- Simulating HDR Lighting with point light sources
- Frequency-Space Image-Based Lighting
- Useful Approximations to image-based lighting
- Real-Time IBL using Graphics Hardware
- Rendering synthetic objects into real scenes
- Choosing a model of the local scene
- Solving for basic scene reflectance properties
- Computing shadows and interreflected light
- Image-Based Lighting Real Objects and Actors
- Reflectance Field Relighting of Human Faces
- A Lighting Reproduction Approach to Live-Action Compositing
- Re-illuminating Live-Action in Post-Production
- Discussion and Q&A (All)
(12:05 - 12:15)
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