Transcript Recovering High Dynamic Range Radiance Maps from Photographs

Recovering High Dynamic Range Radiance Maps
from Photographs
Paul E. Debevec, Jitendra Malik. In SIGGRAPH 97, August 1997
Introduction
• “Dynamic Range” of a scene is the contrast ratio (brightest / darkest parts)
• Recovering High Dynamic Range Radiance Maps
– Multiple Photographs
– Recover … Response function ( film response in exposure )
– Differently Exposed Photographs
• Image-Based Modeling & Rendering
– Image – same ( exposure setting , film response function )
– Recovering reflection models ( BRDF )
– require … absolute Radiance Values
Image Acquisition Pipeline
Film Response Recovery
• The response of a film
Optical Density of film against the Exposure
X  E  t
digital number Z ( development , scanning , digitization process )
Z  f (X )
X  f
1
(Z )
Input – Z ,  t j
f
1
( Z ij )  E i  t j
g  ln f
N
 

i 1
ln f
1
( Z ij )  ln E i  ln  t j
1
P
 [ g ( Z ij )  ln E i  ln  t j ]  
2
j 1
Z max  1

g ''(z)
z  Z min  1
2
Film Response Recovery
• To complete description
- g ( Z mid )  0 ( unit exposure)
- weighting function
w ( z )  z  Z min
 Z max  z
N
 
z  Z mid
for
z  Z mid
Z max  1
P
  {w ( Z
i 1
for
)[ g ( Z ij )  ln E i  ln  t j ]}  
2
ij
j 1
- pixel location ( Zmin ~ Zmax , image )
 [ w ( z ) g ' ' ( z )]
z  Z min  1
2
Constructing the HDR Radiance Maps
• Curve - Radiance values ( associated with g )
ln E i  g ( Z ij )  ln  t j
ln E i 

P
j 1
w ( Z ij )( g ( Z ij )  ln  t j )

P
j 1
w ( Z ij )
Combining the multiple exposures
- reduce Noise, artifacts ( such as film grain )
Constructing the HDR Radiance Map
• Storage
Map  image format
Rendering Synthetic Objects into Real Scene:
Bridging Traditional and Image-Based Graphics with
Global Illumination and High Dynamic Range
Photography
Paul E. Debevec,. In SIGGRAPH 98, July 1998
Introduction
• Scene Radiance & Global Illumination
• High Dynamic Range Image-based model
– Illuminate the NEW objects
• 3 components
– Distant Scene
– Local Scene
– Synthetic Objects
Introduction
• Light Probe
– HDR Panoramic Radiance Map ( near rendered location )
• Light-Based Model
Illuminating Synthetic Objects with Real Light
• Accurately Recording Light in a scene
– Large areas of Indirect Light
– Concentrated areas of Direct Light
• Recovering HDR
– Measure of Scene Radiance
The General Method
• Distant Scene ( a Light-Based Model )
– Light-Based Model
• Accurate measure of Incident Illumination
• ( in vicinity of objects, desired viewpoint )
• Local Scene ( approximate Material-Based Model )
– Interact with the Synthetic Objects
– Geometry, Reflectance characteristic
• Synthetic Object
– variety of Shapes , Materials
Compositing using a Light Probe
• Constructing a Light-Based Model of real scene
• Fully Dynamic Range Omnidirectional Radiance Map
– Radiance measurement  mapped ( geometry of Distant Scene )
• Mapping from the Probe to the scene model
– Mapping coordinates ( ball , world )
– Position, Size, camera Parameter ( location in scene, focal length )
– Assume … Small , Orthograph  good approximation
• Creating Rendering