1. A Computational Darkroom for BW Photography
Soonmin Bae, Sylvain Paris,
and Frédo Durand
Current Status : Resubmission to Siggraph

2. Objectives To enhance black-and-white photographs
“Look” transfer between two images
Direct interpolation and manipulation of the “look”

3. What is the problem?
Direct conversion to B&W yields often unsatisfying results.

4. What can be the “Look”

5. Approaches
Decomposition of an image into large-scale variation layer and high frequency texture layer
Control the global contrast and the local textureness separately
Quantitative characterization
Use image statistics and histograms

6. What we aim at… Control of the visual quality, “look”
Parametric characterization
User-oriented and intuitive method
HDR images

7. What we do not do… Deal with Change Content
Color photographs
Paintings
Change Content
Change Composition
Crop
Select a model or ideal parameters

8. What they do vs. What we do
Tone mapping
Ferwerda et al. 1996;Tumblin and Rushmeier 1993; Ward 1994
Ashikhmin 2002; Tumblin and Turk 1999; Pattanaik et al. 1998; Reinhard et al. 2002
Color2gray
Gooch et al. 2005
Image analogies
Hertzmann et al. 2001; Efros and Freeman 2001; Rosales et al. 2003; Drori et al. 2003
Objective tone reproduction vs. Control of the look
Non-parametric vs. Parametric characterization

9. Challenges Identification of important visual characteristics
Meaningful feature selection
Decomposition
Faithful extraction of the features
Reconstruction
Visual artifact (mainly halos)
Subjective issues
Preference vs. Similarity

10. Quick Technical Overview
large scale
Challenge: differentiate texture from edges.
“textureness”
input
detail

11. Quick Technical Overview
Histogram manipulation (transfer possible)

12. Quick Technical Overview
Histogram manipulation of the “textureness”

13. Quick Technical Overview
before
after

14. Exploring Various Options in a Few Clicks

15. Preliminary Results
Model
Input

16. Open Discussion Should we include the following domains?
Color photographs
Paintings
Which should be pursued?
Transfer vs. Direct parameter modification
Similarity vs. Preference