High Dynamic Range Imaging Samu Kemppainen VBM02S

High Dynamic Range Imaging 2 Introduction Problems with current imaging Basics of HDR images Different techniques –Tone mapping –HDR compression –Image encondings Applications of HDR images

High Dynamic Range Imaging 3 8-bit problem Typical images displayed on screen are 24-bits –8-bits per color component (RGB) –256 different intensity levels Real-world dynamic range is far greater than 256 intensity levels!

High Dynamic Range Imaging 4 Range of luminance : :1 100:1 in the natural world that the eye can accommodate in a single view that a typical CRT/LCD monitor can display (Source: A review of tone reproduction techniques; Devlin, 2002)

High Dynamic Range Imaging 5 What is a High Dynamic Range image? HDRI is an image that has a greater dynamic range that can be –shown on a display device –captured with a camera with just a single exposure The "dynamic range" of a scene is the contast ratio between its brightest and darkest parts (Source:

High Dynamic Range Imaging 6 What is a High Dynamic Range image? Image with a series of images combined into a single high dynamic range image (also called a “radiance map”) They are useful for representing true illumination values in image-based rendering applications And for recording incident illumination and using it to illuminate CG objects for realistic composition (Source:

High Dynamic Range Imaging 7 Recovering High Dynamic Range Radiance Maps from Photographs Acquiring series of differently exposed photographs –Example: sixteen photographs taken at 1-stop increments from 30 seconds to 1/1000 seconds exposure Then combine the photos by using HDR Shop (Source: Recovering High Dynamic Range Radiance Maps from Photographs; Debevec & Malik, 1997)

High Dynamic Range Imaging 8 Recovering HDR radiance maps from photographs Sixteen photographs taken at 1-stop increments from 30 seconds to 1/1000 seconds exposure (Source: Recovering High Dynamic Range Radiance Maps from Photographs; Debevec & Malik, 1997)

High Dynamic Range Imaging 9 Low dynamic range -vs- High dynamic range Original photograph (LDR)Motion-blurred LDR image Motion-blurred HDR imagePhotograph with real motion blur (Source:

High Dynamic Range Imaging 10 How to view HDR images on a LDR device? By using Real-Time High Dynamic Range Texture Mapping –hardware pipeline Using Gradient Domain High Dynamic Range Compression (Source:Real-Time High Dynamic Range Texture Mapping; Cohen et al., 2001)

High Dynamic Range Imaging 11 High Dynamic Range Texture Mapping HDR textures are decomposed into sets of 8-bit textures –They are dynamically reassembled by the graphics hardware’s multitexturing system –or using multipass techniques and framebuffer image prosessing Only two 8-bit textures is needed to be in memory simultaneously (Source:Real-Time High Dynamic Range Texture Mapping; Cohen et al., 2001)

High Dynamic Range Imaging 12 HDR Texture Mapping pipeline (Source:Real-Time High Dynamic Range Texture Mapping; Cohen et al., 2001)

High Dynamic Range Imaging 13 Tone mapping Tone Reproduction and Physically Based Spectral Rendering –Develope for use in tv and photography –Takes advantage of HVS (Human Visual System): the fact that HVS has a greater sensitivity to relative rather than absolute luminance levels (Source: Tone Reproduction and Physically Based Spectral Rendering; Devlin et al., 2002)

High Dynamic Range Imaging 14 (Source: (Dynamic range: :1)

High Dynamic Range Imaging 15 Larson et al., 1997 Low Curvature Image Simplifier (LCIS) method (Tumblin & Turk, 1999) (Source:

High Dynamic Range Imaging 16 Gradient Domain High Dynamic Range Compression Way of rendering HDR images on conventional display –technique is effective, fast and simple –less artifacts than with other methods –it also significantly enhance ordinary images by bringing out detail in dark regions (Source: Gradient Domain High Dynamic Range Compression; Fattal et al., 2002)

High Dynamic Range Imaging 17 Gradient Domain HDR Compression Based on the simple idea –identify large gradients at various scale –attenuate the their magnitudes progressively –a reduced HDR image is then recontructed from the attenuated gradient field (Source: Gradient Domain High Dynamic Range Compression; Fattal et al., 2002)

High Dynamic Range Imaging 18 The Gradient attenuation factors used to compress HDR radiance map (Source:

High Dynamic Range Imaging 19 Gradient Domain HDR Compression (Source:

High Dynamic Range Imaging 20 Example using only two images in Gradient Domain HDR Compression (Source: 1/22 seconds, f81 second, f8

High Dynamic Range Imaging 21 High dynamic range image encodings HDR image have to be encoded to encompass a large range of values Some file formats: –Pixar Log Encoding (TIFF) –Radiance RGBE Encoding (HDR) –SGI LogLuv (TIFF) –ILM OpenEXR (EXR) –Microsoft/HP scRGB Encoding (Source:

High Dynamic Range Imaging 22 Cost (bits/pixel) -vs- benefit (dynamic range) of full-gamut formats (Source:

High Dynamic Range Imaging 23 The difference in the encodings Benefits of log and floating point representations over linear or gamma encodings –24 bits LogLuv format holds more dynamic range than the 36-bit scRGB-nl format (gamma encoding) and even the 48-bit scRGB linear encoding –32 bits LogLuv encoding holds 10 times the dynamic range over the scRGB and scRGB-nl. –The EXR encoding holds 3 times the range of scRGB encoding in the same 48 bits, with much higher precision than any of the other formats (Source:

High Dynamic Range Imaging 24 Image results Some rounding error occur when using log or floating points –ΔE*=2: Detectable under ideal conditions –ΔE*=5: Noticeable in side-by-side images

High Dynamic Range Imaging 25 False color difference view of 24-bit LogLuv (Source:

High Dynamic Range Imaging bit LogLuv32-bit LogLuvEXRRGBE XYZEscRGBscRGB-nlscYCC-nl (Source:

High Dynamic Range Imaging 27 Encoding quality curves (average) (Source:

High Dynamic Range Imaging 28 Some applications of High Dynamic Range images Global illumination techniques (physically- based rendering) Mixed reality rendering (special effects for movies and commercials) Human vision simulation and psychophysics Reconnaissance and satellite imaging (remote sensing) Digital compositing for film Digital cinema

High Dynamic Range Imaging 29 Thank you for listening! Questions? Comments?